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Tampa Bay economy.
n Vol. 2, no. 1 (spring/summer 2001).
Tampa, Fla. :
b University of South Florida, College of Business Administration, Center for Economic Development Research.
Good News for Florida Economic Developers: Florida Payroll Earnings are where they ought to be -- From the Editor -- Update of CEDR's Data Center -- Migration Patterns of the Tampa Bay and the South Central Florida Regions -- Electricity Deregulation: Part I: A Primer, Part II: Regulartory Restructuring in California, Part III: How Florida Should Structure Electricity Deregulation in the Coming Decade -- International Trade Data: What is Available and What Does it Mean?
Tampa Bay Region (Fla.)
x Economic conditions
Tampa Bay Region (Fla.)
Tampa Bay Region (Fla.)
University of South Florida.
Center for Economic Development Research.
By Dr. Kenneth Wieand,Director of the Center for Economic Development ResearchFlorida payroll wages and salaries historically have been below the national average. Chart 1 reports average U.S. wages and Florida wages from 1989 to 1998. Over the period Florida wages were 89% of the national average. Over the same period employment in Florida grew by an average of 2.6% per year and U.S. employment grew by 1.3% per year. The difference in employment growth comes from population in-migration to Florida.11. Earnings Disparity Reflects LowerLiving Costs. Anumber of observers are concerned about the size and duration of the gap between U.S. wages and Florida wages. Many of these observers attribute the wage gap to a preponderance of low skilled jobs in Florida stemming from the state's importance as a tourist destination and as a haven for an older population that demands services but does not participate in the workforce. Starting from this premise, many have recommended policies to restructure Florida's industrial mix toward higher paying industries and higher salary occupations. An editorial by the Chairman of Florida's Growth Management Study Commission, in the April 24, 2001 issue of the Tampa Tribune calls for policies to raise current wage rates as a priority for state economic development policy.2 Existing financial incentive programs use state and local tax refunds to attract businesses that pay their employees high wages. Because state and local budgets balance, a tax refund for someone means that someone else pays higher taxes. While there are legitimate reasons to assist local and state economic development agencies to compete in an imperfect corporate relocation market, subsidies based on wages, especially subsidies that will raise the taxes paid by residents and businesses in the state, are a bad idea. Here's why: Compelling evidence exists that most of the differences in wages across regions and metropolitan areas in the U.S. result from factors that have little to do with the structure of local industries. This is especially true for large diverse metropolitan economies such as Tampa-St. Petersburg-Clearwater, Miami-Ft. Lauderdale, West Palm Beach, Orlando, and Jacksonville. The most important factors leading to differences in regional wages in these areas are: the cost of living, and the size and population density of the metropolitan area. We often refer to wages, after they are adjusted for differences in the cost of living, as "real wages." A recent study finds that, while wages in the South are lower than in the Northeast and Midwest, when adjusted for the cost of living and for amenities wages are actually higher in the South!3Lower Florida wages, seen in this light, are not a problem, but an advantage for the state. Businesses are able to pay lower wages in Florida. This gives them a cost advantage and allows them to create new jobs. Because living costs are lower, Florida workers'real wages are comparable to other states and new employees are attracted to jobs created in Florida. The cost advantages to Florida businesses stemming from lower nominal wages and the fact that the real earnings of Florida's workers are comparable to other states combine to explain the strong growth of population and employment in the state in past decades. Policies that raise wages by increasing taxes will actually reduce the cost of living advantages to Florida residents. Such policies, if followed, will increase employees'wage demands, reduce job formation in the state, and lead to reduced growth and lower economic welfare of the state's residents.THE Tampa Bay EconomyQuarterly Journal of the Centerfor Economic Development ResearchGood News forFlorida Economic Developers: Florida Payroll Earnings Are Where They Ought to Be Continued on page 3
Table of ContentsGood News for Florida Economic Developers: Florida Payroll Earnings Are Where They Ought to Be............................................1 From the Editor..............................................................2 An Analysis of International Trade in the Tampa Bay Area..............................................8 Update of CEDR's Data Center..................................12 Migration Patterns of the Tampa Bay and the South Central Florida Regions....................13 Electricity Deregulation: Part I: APrimer......................................................22 Part II: Regulatory Restructuring in California......25 Part III:How Florida Should Structure Electricity Deregulation in the Coming Decade..........26 International Trade Data: What is Available and What Does It Mean?............29CEDRStaffDr. Kenneth Wieand............................................Director Dr. Dennis Colie................................Associate Director Dodson Tong..............................................Data Manager Alex McPherson..............................................Economist Gina Space......................................................Economist Nolan Kimball..Coordinator of Information/Publication Anand Shah................................................Web Designer Carol Wallace........................................Student Assistant Petia Nikolova......................................Student Assistant 2 Our Sponsors:The Tampa Bay Partnership THETampa Bay Economy From The Editor. . This issue of The Tampa Bay Economy contains good news about wages in Florida. There is also a three-part article on electricity deregulation that addresses the problems that California is experiencing and what can be done to prevent the same problems from occurring in Florida. Two articles on international trade data, an article on migration patterns of Tampa Bay and the South Central Florida regions, and an update on CEDR's data center round out the articles for this journal. This issue of the journal is combined for Spring/Summer 2001. Inside the issue are the data inserts for both, 1st and 2nd quarters of 2001. Congratulations to CEDR for winning the following awards in the first six months of this year: Best of Class Award for Newsletter/Newspaper/Magazine and Excellence Award for Web Sites/Multimedia/Other from the American Economic Development Council. Honorable Mention Award for "Financial Services in Tampa Bay Growth, Impacts and Opportunities" from ACCRA, a national economic development research organization. CEDR offers the only basic economic development course in Florida that is accredited by the International Economic Development Council. This year's course will be held at the Hilton Garden Inn in Ybor City. Course dates are November 4-9, 2001. For more information regarding the course, contact CEDR at (813) 905-5854.
2. Analyzing Earnings Differentials. CEDR studied average earnings for 198 urban places in the United States. To obtain all the data needed it was necessary to use 1996 data. As Chart 1 shows, the wage disparity has not changed over time, and we believe that the relationships that held between wages and location, size, industry structure and demographic composition continue to hold in 2001. The places covered in the study vary in location, size, and industry structure. Included in the sample are 11 Florida cities in Table 1. The average 1996 annual earnings of workers in all 198 places was $25,472, ranging from $18,551 in Myrtle Beach, South Carolina, to $40,089 in New York City. CEDR constructed a statistical model to explain the variation in the average earnings across all of the 198 areas. The first factor we consider is the cost of living. The cost of living is important because workers encountering higher living costs will demand higher wages. If employers are unable to pay them, employees will begin to move to other areas where either wages are higher, the cost of living is lower, or both. The most complete comparable price index for comparing city living costs is produced by ACCRA. The ACCRA index provides comprehensive indices on components of consumer expenditure and an aggregate, or overall, cost of living index that is a weighted-average of all the components. The ACCRA Good News for Florida Economic Developers: Continued from page 1 3Continued on page 4
4Good News for Florida Economic Developers: Continued from page 3 index is available for over 300 U.S. cities. We used ACCRAinformation from the 3rd quarter of 1996. Predictably, adjusting nominal wages for the cost of living results in lower adjusted wages in high cost-of-living areas such as New York City, and in higher adjusted wages in low cost of living areas like Anniston, Alabama. Table 1 reports annual earnings for selected cities, the cost of living index, and earnings adjusted by the statistical model. Note that adjusting for the cost of living in very high-cost cities, such as New York City; causes wages to fall dramatically. (New York City is actually over-adjusted, as the ACCRAindex is only available for Manhattan, where costs are higher than in the other boroughs of the City.) Adjusted wages for most Florida cities rise. (See Table 1 on previous page) The next factor we adjust for is the population size of the metropolitan area. Population is an interesting factor. We would expect that the cost of living would be higher in larger cities as commuting costs and land values rise. But cost of living adjustment has already been applied. The question to be asked is "How can a large city, with high cost of living, compete for businesses that can locate in any number of places?" (Examples are financial headquarters on Wall Street or fashion houses on Madison Avenue in New York City.) The question is puzzling. Economists assume that there must be scale economies associated with large cities that give businesses an edge to offset their higher labor and real estate costs. Indeed, the model predicts that, other things equal, firms in metropolitan areas that have between 250,000 and 500,000 residents are able to pay annual wages that are $674 higher than cities of less than 250,000 residents. Cities with populations between 500,001 and 1,000,000 persons can pay $205 more than cities with a quarter to a half million residents, and cities that have between 1 and 3 million residents can pay annual wages of $660 more than the next smaller group. Firms in cities with populations of between 3 and 7 million can pay wages that are $1371 more than the next smaller group. And the model predicts that firms in the very largest cities, with populations of over 7 million, are actually less competitive than smaller cities and, and can pay wages that are $474 less than the smallest cities! Nominal wages unadjusted for cost-of-living, remain higher, but adjusted wages are lower in the largest cities. Table 2 reports payroll earnings in the selected cities adjusted for both cost of living and population. In order to make our comparison, we assume that all cities have populations between 1 and 3 million persons. Salaries of the smaller cities, and of the largest class of cities as well, are adjusted upward. Wages paid by firms in cities with 3-7 million are adjusted down by $1,371. (See Table 2) Note that wage disparity between Florida cities and cities in other states shrinks further when city size is taken into account.
Continued on page 6 The average wage is a weighted-average of wages in each of 10 1-digit Standard Industrial Classification (SIC) industry divisions.4Historically different industries have paid different wages on average. Retail trade and services, for instance, have paid lower-than-average wages. Mining, manufacturing, and communications, transportation and public utilities have paid higher-than-average wages. One would therefore expect cities with concentrations of lower paying industries to have lower average wages and cities with concentrations of higher paying industries to have higher average wages. Table 3 further adjusts annual earnings figures for industry structure. We compute average earnings as though each place has the U.S. average industry structure. Adjusted for industry structure, Ft. Walton Beach, a retirement community having a large percent of service workers, gains in its average earnings. Boston, having a large fraction of higher paying financial services and manufacturing employment, is adjusted downward. Most large metropolitan areas have strongly diversified employment bases. Wages in these places are not strongly affected by adjustment for industrial structure. (See Table 3) We make one final adjustment for educational attainment of the workforce. Highly educated workers command large earnings premia. And indices of educational attainment vary widely across cities.5Table 4 further adjusts for education. (See Table 4 on page 6) Three large northeastern cities, Boston, New York and Philadelphia, and the large metropolitan area of Los Angeles on the West Coast, are rated very highly by the education index we use. When adjusted for education, earnings fall dramatically in these cities. Florida cities in our sample that have low education indices experience increases in their earnings indices. 3. How Well Does the Model Predict Florida Wages? The model used for this analysis includes other variables, such as unionization, state-local tax burden, and ethnic composition, to explain wages. When all variables are considered, one may ask how well the model predicts actual earnings. Table 5 provides this information for all 13 Florida places included in the sample. The second column reports actual 1996 earnings. Column 3 gives the model's predicted earnings for each place and Column 4 provides the model's prediction errors. (See Table 5 on page 7) The model over-predicts Orlando's earnings by $2,245, and under-predicts earnings in West Palm Beach by $2,807. Both of these figures are well within standard prediction errors of the model, which has a standard error of $1,705. Earnings in Tampa Bay were over-predicted by $552, or about 2%. On average, the model over-predicts Florida earn ings by about 1.5%. The model may not capture all the factors that lead to wage dispersion, and this 1.5% could represent the effect of Florida's vaunted amenities. But complex economic phenomena such as payroll earnings are expected to exhibit some randomness across space. The prediction errors are relatively small. They may represent nothing more than our economy's inability to eliminate short run variations in labor market conditions across MSAs. Overall, the model does a good job of explaining variations in the wages across the U.S. and within Florida, explaining over 80% of the variance in unadjusted earnings. 5
6Good News for Florida Economic Developers: Continued from page 5 4. Conclusions. While payroll earnings vary widely across metropolitan areas, earnings disparities fall dramatically when adjusted for factors including the cost-of-living, population, industry structure, and education. The standard deviation of unadjusted earnings, a measure of dispersion within the sample of 198 cities, falls by half, from $3,349 to $1,705 upon adjusting for these four factors. Examination of Tables 1 4 indicates that much of the observed disparity in wages is eliminated when the four factors are controlled. Average unadjusted earnings in 11 comparison cities were $31,336 in 1996. In 11 Florida cities unadjusted earnings were $24,482-a gap of $6,854, or 22% of the comparison city average. Upon adjustment for the four factors, wages in the 11 comparison cities were $27,988 and in the 11 Florida cities $26,686-a gap of $1,302, or 4.6% of the comparison city average. Analysis of the earnings figures for the U.S. and Florida should make us skeptical of policies designed to "reduce the wage gap" by attempting to engineer changes in a region's industrial structure. Table 3 demonstrates that industry structure in larger diversified Florida cities, explains from $500 to $1,000 of average earnings. By contrast, Florida's relatively low cost of living compares favorably with the comparison cities. Florida cities gain $18 but the comparison cities lose $1,700 when adjusted for cost-of-living. The evidence now is that Florida's higher population growth is mainly a result of lower cost-of-living in the state. Population growth has been closely linked to growing state employment. Businesses that can pay lower wages are more competitive. They can create the jobs filled by new residents migrating into the state. Lower cost-of-living means that employees can accept lower money wages without being worse off in real terms. Thus, lower money wages are consistent with growing state employment and population. On the other hand, educational attainment has a significant impact on earnings. Indeed, the higher earnings of very large cities appear to stem partially from the fact that they attract highly educated workforces. Education statistics indicate a net movement of more highly educated persons from smaller cities to larger ones. Growth management is the arena in which economic development and issues of quality of life will struggle in coming years. The challenge facing businesses, state, and local governments in coming years is to accommodate continuing population and employment growth, while keeping Florida's cost-of-living low and maintaining the quality of life that Floridians expect. Thus, the State's success in providing quality education and infrastructure in a cost-effective manner is key to sustainable economic development.
7 Appendix: The estimating model used in this paper. The model consists of three equations that are jointly estimated. The variables "payroll earnings", "labor force participation rate" and "cost of living" are jointly estimated because the three variables interact together as part of the operations of regional labor markets. The equations are: !"# ""!$$% &$%$ $% % %'() "*+, (" "#!" $$% &$$% *"#% ./" %"$%"0 "0%"/ %"/ 0/% "( 0 / Results are reported here only for the earnings equation. In the earnings equation the variable TCU is transportation-communications-utilities, and FIRE is financeinsurance-real-estate. R-squares are: Earnings .81; Cost-of-living .66; Laborforce-participation .66. End Notes.1As part of a nation-wide program reporting unemployment insurance payments, all enterprises with workers subject to Florida's unemployment insurance program are required by the Florida Agency for Workforce Innovation to report employment and payroll on a monthly basis. Individual company reports are the basis for Florida's ES-202 data set. Each state operates an ES-202 program. Data from state ES-202 programs allows us to track and compare employment and employee earnings by standard industrial classification codes for U.S. counties and metropolitan areas.2Fredrick Leonhardt, "Florida's economy is study group's No. 1 priority," Tampa Tribune, Tuesday, April 24, 2001, Nation/World p. 9.3Dumond, M, Hirsch, B, MacPherson, B., "Wage differentials across labor markets and workers: does cost of living matter?", Economic Inquiry v.37 #4, October, 1999. Pp 577-98.4These industry divisions are; Agriculture, Mining, Construction, Primary Goods Manufacturing, Finished Goods Manufacturing, Communications Transportation and Public Utilities, Wholesale Trade, Retail Trade, Finance Insurance and Real Estate, and Services
8An Analysis of International Trade in the Tampa Bay Area By Gina B. Space,Economist with the Center for Economic Development Research This article utilizes available export data to examine Tampa Bay's metro area level export data. The International Trade Administration's metro area level data, based on the Exporter Location (EL) series identifies countries and world regions that import goods from Tampa Bay area businesses. The data are available for the Tampa-St. Petersburg-Clearwater metro area and the Lakeland-Winter Haven metro area. World region and country-level data are not available for the SarasotaBradenton metro area, but the aggregate value of exports is released on an annual basis. (Note: The Origin of Movement (OM) series data are not collected at the substate level so this analysis applies only to export activity, not production.) Chart 1 shows the aggregate levels of export activity for the three metro areas from 1993 to 1999. In 1993, the Sarasota-Bradenton and Lakeland-Winter Haven MSAs exported about the same value of merchandise, just over $185 million. However, from 1993 to 1998, LakelandWinter Haven's export activity outpaced SarasotaBradenton by a margin of 4 to 1. Lakeland-Winter Haven's export increase is probably attributable to increased sales of agricultural and chemical products. The Tampa-St. Petersburg-Clearwater MSAexports grew over 85%, from $1.3 billion in 1993 to $2.4 billion in 1999. Taken as a region, the Tampa-St. PetersburgClearwater MSAaccounts for 84% of total exports, the Lakeland-Winter Haven MSAaccounts for 9% and the Sarasota-Bradenton MSAaccounts for 7%. (See Chart 1 on next page) Exports for the entire Tampa Bay Region (the three MSAs combined) grew 71% from 1993 to 1999. Since detail data is not available for the Sarasota-Bradenton MSA, the following analysis applies to the aggregate of the Tampa-St. Petersburg-Clearwater and Lakeland-Winter Haven MSAs, referred to hereafter in this article as Tampa Bay. However, since Sarasota-Bradenton is a relatively small amount of the total export value, the analysis would change only slightly if detail data were available. Chart 2 displays the value of Tampa Bay's exports by the region of the world to which the goods were shipped. The most striking information presented in this chart is (1) the dominance of Asia as Tampa's largest export market and (2) the $200 million plus decrease in exports to Asia between 1995 and 1996. (See Chart 2 on next page) When the available export data are plotted by country, China was the largest export destination in 1995 and showed the most obvious decrease in the value of goods imported from Tampa Bay in 1996. The data also show merchandise exports to India dropped significantly in 1996. In fact, China's and India's imports from Tampa Bay decreased $239 million and $83 million, respectively, between 1995 to 1996, for a combined total decrease of $322 million. Exports to all of Asia declined during 1995-1996 (by $274 million), but by less than the fall in exports to China and India. Thus, while Tampa Bay's merchandise exports to the rest of Asia were increasing from 1995 to 1996, China and India imported so much less from Tampa Bay that the overall effect was a net decrease in exports to Asia. Because industry and product data are not available at the metro area level, we must turn to Customs Management Center (CMC) level data to try to understand what caused the massive decrease in export value to China and India. (Note that CMC data covers numerous ports over a much larger geographic area than the Tampa Bay Region and may not always be representative of Tampa Bay's exports. See "International Trade Data: What is Available and What Does it Mean?" in this issue of The Tampa Bay Economy .) CMC-level export data show that exports from the North Florida CMC to China decreased from $856 million in 1995 to $501 million in 1996, a drop of $355 million, larger than the decrease in the ELseries data from Tampa Bay. China's imports of goods classified under Chapter 31 of the Harmonized Tariff Schedule (HTS) decreased $374 million, exceeding the total decrease from the CMC, and most likely accounting for the decrease in Tampa Bay's exports as well. Chapter 31, broadly classified as fertilizers, includes natural phosphates, superphosphates and ammonium phosphates, all of which are produced in and exported from the Tampa Bay Region. Chapter 31 exports make up the vast majority of goods exported to China through the North Florida CMC, rising from 83.5% of all exported goods in 1993 to 99.2% in 1999. The next largest export value decrease was in machinery and mechanical appliances and was less than 1/2 of one percent of the decrease in Chapter 31 value. Exports to India from the North Florida CMC decreased $140 million over the same time period, also exceeding the drop in Tampa Bay's export value from the ELseries. Similar to China, nearly all of the goods exported from the North Florida CMC to India are Chapter 31 fertilizers. The fraction of total export value attributable to fertilizers rose from a low of 89% in 1996 to 99% in 1998. In 1995, the decrease in the value of Chapter 31 goods exported from the North Florida CMC to India exceeded the total decrease in all CMC exports to India by $3 million. The next largest value decrease occurred in organic chemicals and was slightly less than 0.3% of the decrease in fertilizer value.
The substantial decrease in phosphate exports was due in a large part to the dramatic increase in the price of diammonium phosphate from 1994 to 1995. Consequently, countries purchased higher than normal amounts in 1995 to protect against future price increases in 1995 and reduced purchases in 1996 in order to clear inventories. Monetary adjustments, such as the devaluation of the Indian rupee in 1996, also contributed to the depressed international market in phosphates and fertilizers. Thus, it can be generally concluded that a decrease in phosphate fertilizer exports to China and India account for the overall decrease in the value of merchandise exports from Tampa Bay between 1995 and 1996. It is true as well that the economics that affect the phosphate industry, especially the world demand for phosphate-based fertilizers, have a significant impact on the value of goods exported from the North Florida CMC and on Tampa Bay's merchandise export value. Customs district data and Florida state data show another dramatic decrease in phosphate exports for 2000. (Metro area level export data have not been released for 2000.) Therefore, it is expected that the ELseries data for total exports from Tampa Bay will show a significant decline in 2000 when they are released. Broadening the analysis beyond phosphate fertilizers, the Tampa Bay Region's 10 largest export markets in 1999 (the available data does not list all countries separately) are ranked in Table 1 on the next page. These countries have consistently comprised the top ten export markets since 1993, except for a few occasions: two years India ranked 11th; and one year France ranked 11th. Canada and China have been the9 Continued on page 10
only countries to rank as either the first or second largest export market since 1993. Using the same data series, the Exporter Location series, Florida's ten largest export markets are also listed in Table 1. This data is from the year 2000 ELseries data, whereas the Tampa Bay data is from 1999. (See Table 1) Although Tampa is geographically positioned in close proximity to many Latin American countries, and several of these countries appear in Florida's list of top ten export markets, currently the region's best export markets are the two NAFTAcountries, Asia and Europe. (Note that Mexico, a Latin American country, is included under the NAFTAcountries. This is by ITAdefinition and is probably intended to assist in monitoring and evaluating trade policy.) Why are Tampa's export markets different from Florida's and why are the closest markets not the largest markets? In order to answer the questions, we evaluate Tampa Bay exports relative to Florida's. Since we are unable to determine exactly what products are being exported from Tampa Bay to our top export markets (recall that the data is not released by the Census Bureau), we compare Florida's merchandise exports to Tampa Bay's market share of state output of such merchandise. Using employment as a proxy for production, we calculate: (1) the percentage of regional employment to statewide employment per 2 digit SIC (or major industry) of export goods and (2) the overall percentage of regional employment to total state employment. The regional market share is then defined as the ratio of the employment percentage for a given major industry to the overall regional employment percentage. We refer to this ratio as the market share ratio, where for export industry i : An Analysis of International Trade in the Tampa Bay Area Continued from page 9 IndustryiExportShareTampa Bay= This ratio is often referred to as the "location quotient" for industry i A market share ratio larger than one indicates Tampa Bay has a larger percentage of workers in a major industry than is expected if the distribution of industry workers is proportional across regions. We can interpret this to mean that Tampa Bay has a specialization in that major industry relative to other areas in the state. Similarly, a ratio less than one indicates Tampa Bay does not specialize in producing goods in the major industry and a ratio equal to one indicates Tampa Bay produces such goods in equal proportion to the average Florida region. Table 2 shows Tampa Bay's market share ratio for the major goods producing export industries. (See Table 2 on next page) Now that Tampa Bay's market share ratios are known, it is necessary to examine which major industries are most important in Florida's trade. Florida's top five major goods exporting industries and the value of goods exported in 2000 are listed in Table 3 below. This data is aggregated from a list of Florida's top 50 export markets, by value of merchandise exported. (See Table 3 on next page) The five industries listed above consistently make up the largest value of goods exported to Florida's top ten markets. These industries account for over 50% of the value of exported goods to nine of Florida's top ten export markets and over 75% of the value of exported goods to six of Florida's top ten export markets. The Dominican Republic, for which the five industries 10 IndustryiEmploymentTampa Bay IndustryiEmploymentFlorida TotalEmploymentTampa Bay TotalEmploymentFlorida TOP 10 EXPORT MARKETS
constitute only 38% of export value, is the most diverse of Florida's top export markets. Moreover, these five major industries account for nearly 70% of the value of all merchandise exports to Florida's top fifty export markets. Clearly, SICs 28, 35, 36, 37, and 38 heavily influence Florida's export patterns and help determine the top export markets. So how does Tampa Bay fare in these five major industries? Tampa Bay's market share ratio for four of the five industries is greater than one, indicating a specialization. (Tampa Bay does not have a relative specialization in producing transportation equipment (SIC 37), according to the market share methodology.) However, only two of these five industries have a strong degree of specialization relative to the other major industries in Tampa Bay. Not surprisingly, chemical and allied products, which include phosphate and fertilizers, ranks third as Tampa Bay's most specialized industry. SIC 38, scientific/ professional instruments, photographic/optical goods, watches & clocks, ranks seventh. So while these five export industries may not be Tampa Bay's strongest suits, there is still enough regional specialization to expect that the countries importing these goods would be among the largest export markets for Tampa Bay. Especially notable for Florida's large Latin American markets is that the top five industry exports to Argentina and Columbia consist entirely of the five industries listed in Table 3. For Venezuela, the six top industry exports are those same five, plus rubber and miscellaneous plastics. Only the Dominican Republic imports a diverse enough basket of goods for the top five industries to be diluted among the top 13 import industries. This analysis shows that Tampa Bay does specialize in producing goods in Florida's most important export industries. And this most likely accounts for the fact that six of Tampa Bay's top ten export markets are the same as Florida's. The remaining four, China, India, Netherlands and France do not appear on Florida's list. Why? China and India, as shown above, mostly import phosphate fertilizers from Florida, which Tampa Bay specializes in and most of which is shipped through Tampa's seaport. The Netherlands and France are more difficult to explain. Because we do not know for certain what these countries are importing from Tampa Bay, we cannot know for certain why they constitute such large export markets. We can speculate, however, that since the ELseries measures the value of goods exported by the location of the entity that effects the export, Tampa Bay must have strong business relationships with companies and individuals in the Netherlands and France. However, this also implies that the goods produced in Tampa Bay in industries where Tampa Bay has a high market share ratio are not being exported by businesses and individuals in Tampa Bay. This leads to two possible conclusions: (1) the goods produced in Tampa Bay are sold in the U.S.; and/or (2) the goods produced in Tampa Bay are being exported through businesses and individuals in other parts of Florida. If the second is true, it presents a challenge to the Tampa Bay community and economic developers to create efficient export channels to discourage the leakage of exports and promote the business associated with exporting these goods. If detailed ELand OM series export data were available by zip code or metropolitan area, a much clearer picture of Tampa Bay's export trade would be available. This data would clarify whether Tampa Bay's merchandise are being exported internationally or sold domestically within the U.S., and if so, from which region in Florida the transactions are conducted. It would also assist economic development professionals in designing, implementing and targeting effective international trade programs. 11 FLORIDA'S TOP EXPORT INDUSTRIES TAMPA BAY'S INDUSTRIES MARKET SHARE
12Update on CEDR's Data CenterBy Dr. Dennis Colie,Associate Director of the Center for Economic Development Research There has been a major addition to CEDR's on-line Data Center. Data for determining migration patterns are available. Go to http://cedr .coba.usf.edu and "Query CEDR Databases." The Regional and State database section now includes MIGRATION County-to-county migration flow data shows migration patterns, by county and time span, based on year-to-year changes in the addresses entered on individual income tax returns. This database uses income tax return filings as a proxy for location of residence. Changes in the locations of filings are used as proxies for changes in location of residence. For instance, when a primary taxpayer's Social Security Number (SSN) appears on a return filed in base year 1996 (for the tax year 1995) matches the SSN on a return filed in 1997 (for tax year 1996), the county of residence is compared to decide if they were the same. If the county addresses match, the taxpayer is a non-migrant. If the county of residence of the return filed in 1996 does not match the county of residence of the return filed in 1997, the 1997 taxpayer is considered an out-migrant from the 1996 county of residence and inmigrant into the 1997 county of residence. Migration time spans available are: 1995-1996, 19961997, 1997-1998, and 1998-1999. The years shown represent the years in which the tax returns were filed. There are three subsets of the data: inflow, outflow, and net migration. The inflow subset shows the number of inmigrants into a selected Florida county by place of origin. The outflow subset shows the number of outmigrants from a selected Florida county by place of destination. The net migration subset is total in-migrants minus total out-migrants for each Florida county and for the state of Florida. The county-to-county migration flow data is compiled by the U.S. Census Bureau from the Internal Revenue Service's Individual Master File system. The counts for personal exemptions represent the actual number of individuals who were reported on a tax return. These numbers may differ from year to year due to births, deaths, marriages, and dependents no longer being counted as exemptions. The number of exemptions does not take into account any special provisions for blindness or age 65 or older; these factors are accounted for in the tax computation portion of a tax return, but not included in the migration data. Because not all persons file a tax return in a given year and because the number of exemptions claimed on a tax return do not necessarily reflect persons residing at a primary taxpayer's address, CEDR has applied an adjustment factor to the data. Over the time period from 1995 to 1998 the average ratio of Florida's estimated population to the total number of exemptions claimed by primary taxpayers with Florida addresses was 1.18204. Exemptions reported on applicable tax returns are multiplied by the adjustment factor, 1.18204, to obtain the migratory approximations reported here by CEDR. In addition to the migration data, the Regional and State database section continues to make available the following: Cost of Living. This data set provides relative costs of living for Florida's 67 counties and is released annually by the Florida Department of Education. The average cost of living in a given year (1993 to 2000) among Florida's 67 counties is set at 100% and then each Florida county's relative cost of living is expressed relative to 100%. Education Indicators. The indicators in the data set are graduation rates, drop out rates, SATscores, average class size, and per pupil expenditures for Florida's public high schools. The Florida Department of Education distributes the data. CEDR presents the data organized by county and covering three academic years beginning with 1996-1997. ES202. This data set is a Bureau of Labor Statistics (BLS) sponsored collection of job and wage data from all employers participating in Florida's unemployment insurance program. It is organized by 1-digit level Standard Industrial Classification (SIC) codes (and totals for all SIC codes) and describes the number of units (i.e. an establishment designated as a single reporting unit for the unemployment insurance system), the number of covered employees, total wages of those employees, and average wages. The data set is partitioned for each Florida county and provides monthly data (by quarter) from first quarter 1988 to second quarter 2000. Aversion with annual data from 1988 to 1999 is also available. Gross Sales. This data is obtained from the Florida Department of Revenue and is intended as a measure of economic activity. Gross sales are the sum of taxable and non-taxable sales as reported by businesses to the Florida Department of Revenue. The Florida Department of Revenue reports gross sales and taxable sales to CEDR by "kind" code. In order to protect the confidentiality of businesses reporting to the Florida Department of Revenue, CEDR has aggregated certain kind codes and converted the aggregations to categories. The data set is partitioned by Florida county and provides monthly data from 1994 to 2000. Housing Permits. This data set of construction authorized by building permits is distributed by the Manufacturing and Construction Division, Bureau of the Census. The data set is primarily based on reports submitted to the Bureau by local building permit officials in response to a mail survey, although some data may be generated by Census Bureau interviewers or imputed from past data. The data on CEDR's web site is organized by state, by county, and by Metropolitan Statistical Area (MSA) for each month of a year from January 1996 to December
Migration Patterns of the Tampa Bay and the South Central Florida RegionsBy Dr. Dennis Colie, Associate Director of the Center for Economic Development Research The addition of countyto-county migration flow data to the CEDR web site is announced in a companion article in this issue of The Tampa Bay Economy The companion article is titled "Update on CEDR's Data Center." In this article, we illustrate the use of migration flow data. When interpreting the data, some caution is warranted. Migration flows are imputed from the numbers of exemptions claimed by taxpayers on their federal income tax returns when there is an address change on year-to-year filings. There are reasons migrants may not be precisely counted: 1) a person for whom an exemption is claimed may not reside in a primary taxpayer's household, 2) households may own or rent more than one residence, e.g. "snow birds," and file tax returns from different addresses year-to-year, and 3) some households may not file a federal income tax return. Tax returns are a poor proxy for non-U.S. citizens, particularly migrant workers who frequently relocate. CEDR applies an adjustment factor to the number of exemptions to improve the accuracy of the estimates of migration flows. As pointed out in this issue's feature article, "Good News for Florida Economic Developers: Florida Payroll Earnings Are Where They Ought to Be," nominal wages are lower in Florida than in many other parts of the U.S. 2000. The data describe the number of units and aggregate value for which building permits have been issued by single-family, 2-family, 3&4-family, and 5-family units. Local Area Unemployment Statistics (LAUS). This labor force data set is prepared monthly by the Bureau of Labor Statistics (BLS) and describes labor force participation, employment, unemployment, and unemployment rate by county of residence. (Data is also included by Florida MSA.) The self-employed are counted as employed persons in the LAUS data. The LAUS estimates are based on a combination of data from the Current Population Survey (CPS), unemployment insurance claim data, the Current Employment Statistics (CES) survey of establishments, and ES-202 data. Statewide and Florida counties'data are available. The data can be displayed by month from January 1990 to December 2000. Annual averages are also available. Personal Income, perCapita Personal Income, and Population. These three data sets are organized by county, or by MSA, per year and are released annually through the Regional Economic Information System (REIS) of the Bureau of Economic Analysis (BEA). The data is based on place of employment and reflect annual averages. In producing REIS, BEAmakes use of data that are byproducts of the administration of various federal and state programs, including unemployment insurance, Social Security, federal income taxes, veterans benefits, and military payroll. Hence, the REIS data series, which includes farming and non-farming, military and civilian, proprietorships (i.e. self-employment) and wage and salary employment, are more comprehensive than ES202 data that covers nonfarming and salary employment only. BEAdefines Personal Income as the current income received by persons from all sources (including investment income and transfer payments) minus their personal contributions for social insurance. Personal income includes both monetary income (including non-paycheck income such as employer contributions to pensions) and non-monetary income (such as food stamps and net rental value to owner-occupants of their homes). The REIS county and MSAdata are issued about 16 months after the year in which the observations were made. Currently the CEDR's data center has this information from 1969 to 1998. Other items that can be found at CEDR's web site are reports of recent studies and publications as well as links to other sites containing data of interest for economic developers. In addition, you can find information about USF's 25th Annual Economic Development Course to be held at the Ybor City Hilton, near downtown Tampa, on November 4 to 9, 2001. CEDR's on-line data center continues to garner wide interest. Over the six-month period from December 2000 to May 2001, the web site received an average of 7,282 hits per month (excluding CEDR staff hits). This was an increase of 841 hits over the previous period, June to November 2000. During the most recent period, users remained at the site for an average of 14.3 minutes per visit. Continued on page 1413
14However, when adjusted for a lower cost of living, Florida's workers enjoy a real wage, i.e. spending power, on a par with, or better than other locations, particularly the Northeast and Midwest states. Coupled with a consideration of Florida's other amenities such as a very moderate climate and excellent beaches, the labor market appears to function as may be expected from economic theory. The article's author, Dr. Ken Wieand, concludes, "The cost advantages to Florida businesses stemming from lower nominal wages and the fact that real earnings of Florida's workers are comparable to other states combine to explain the strong growth of population and employment in the state in past decades." Between 1997 and 1999, the Tampa Bay region experienced a net migration of about 118,000 people.1Inmigration accounts for all of Tampa Bay's population growth. (Over the 1997 to 1999 time span deaths in excess of births averaged 738 per year.) Annual population growth has averaged 1.3% and is expected to continue at that pace.2(See Chart 1 on previous page) In 1997, 1998, and 1999, Pasco County had the highest net migration in each year. Manatee County had the fewest net migrants in 1997, while Hernando County had the fewest in 1998 and 1999. (See Table 1) The origins of in-migrants and destinations of outmigrants are of further interest. Much of the Tampa Bay county-to-county migration is among adjacent counties. Table 2 displays the top five origins for in-migrants and the top five destinations for out-migrants for each of Tampa Bay's seven counties. (See Table 2 on page 19) Interestingly, Suffolk County, New York, regularly makes the top-five list of places of origin for in-migrants to Hernando and Pasco Counties. Cook County, Illinois, often makes the top five list for in-migrants to Pinellas and Sarasota Counties. There is also a consistent migration, in and out, between Tampa Bay's counties and Miami-Dade and Orange Counties, and to a slightly less extent between Tampa Bay and Broward County. And, although not on the top-five list, the presence of MacDill Airforce Base has a measurable effect on the migration flows of Hillsborough and Pinellas counties. In the 1997 to 1999 time span, Hillsborough County became the home of an estimated 3,544 persons who were previously listed at APO/FPO addresses.3Over the same period, 2,233 persons left Hillsborough County for APO/FPO destinations. Similarly, Pinellas County received 913 people from APO/FPO addresses and lost 624 people to APO/FPO destinations. In contrast with Tampa Bay's net migration of nearly 118,000 and average annual population growth of 1.3% between 1997 and 1999, the South Central Florida region experienced a net migration of about 15,189 people and an annual population growth rate of 1.2%.4The population increase in the South Central Florida region from 1997 to 1999 was 15,426 persons, of which about 90 percent was due to net migration.5However, discounting Polk County's population increase of 14,671 persons, the population increase of the other counties is estimated at 755 persons over the span from 1997 to 1999. (Over the 1997 to 1999 time span births in excess of deaths averaged 1,530 per year in the region. Excluding Polk County, births in excess of deaths averaged 72 per year.) (See Table 3 and Chart 3 on page 20) Like the Tampa Bay region, much of the county-tocounty migration of the South Central Florida region is among adjacent counties. However, in contrast with Tampa Bay there is no county outside Florida that makes the top-five list of places of origin for in-migrants to a South Central Florida county. Table 4 shows the top five origins for in-migrants and the top five destinations for out-migrants for each of the South Central Florida's five counties. (See Table 4 on page 21) Migration Patterns of the Tampa Bay and the South Central Florida Regions Continued from page 13 Continued on page 20
16 Please tear at perforation.
17 Please tear at perforation.
19 Table 2 Tampa Bay Counties Origins and Destinations
We can also examine the number of migrants moving from outside Florida (an interstate move), from within Florida (an intrastate move), or from outside the U.S. (a foreign move, which includes moving from an APO/FPO address) into the Tampa Bay region. (See Table 5) Each year, 1997 through 1999, there were more people moving into Tampa Bay from outside the state of Florida than the number making an intrastate move. Among the Tampa Bay counties, the only county experiencing the opposite of this trend was Pasco. Pasco County received more intrastate migrants than interstate migrants each year. And, while the most populous county in Tampa Bay, Hillsborough, is also the destination of more out-ofstate migrants than any other county in the region, Pinellas County annually receives the highest proportion over 60% of total migrants from outside the state. Although in the aggregate the South Central Florida region has had more interstate than intrastate in-migrants, this phenomenon is primarily attributable to Polk County.6Besides Polk, only Highlands County received more interstate than intrastate in-migrants. Also, readily noticeable is the paucity of in-migrants from foreign addresses, except for Polk. (See Table 6 on next page) The annual average, from 1997 through 1999, of the South Central Florida region's in-migrants has been 48.5% originating within the state of Florida and 50.7% originating outside the state. Less than 1% migrate into the region from a location outside the U.S. An examination of the numbers of migrants and migration patterns helps to explain a region's rate of population change and, to some extent, the changing composition of the population. Economic developers, local and regional planners and political decision-makers will allocate scarce resources more efficiently and improve growth management strategies when migration flow patterns are incorporated into analyses. 20Continued on page 22 Migration Patterns of the Tampa Bay and the South Central Florida Regions Continued from page 14
Table 4 South Central Florida Counties Origins and Destinations 21
Electricity Deregulation: Part I: APrimerBy Dr. Kenneth Wieand,Director of the Center for Economic Development Research Recent innovations in the technology of electric power generation have opened the door for competition in regional electricity pricing. Policymakers in over twenty states have responded by experiments in deregulation. Recent developments associated with deregulation in Californiarolling "blackouts", financial trauma for California utilities, and charges and countercharges as to the source of the state's difficultieslead to concern about the role of deregulation of the price of electric power in the future. This article examines the possibilities and pitfalls of electric utility deregulation. The Production Cycle of a Private Corporation. The majority of electric utilities in the U.S. are privately owned corporations. Economists recognize that private corporations in a competitive environment contribute to national economic welfare by producing goods and services desired by the public at a lower cost in resources than governments can achieve. They do so through private markets that allocate resources efficiently to achieve lower product costs. Private corporations operate efficiently partly because they face market competition in all phases of their production cycles. The following diagram, titled "the private corporation" illustrates the productioncycle of a private corporate enterprise that operates in competitive markets. The diagram identifies the owners as individuals and organizations who own the firm's outstanding shares of common stock. Shareholders have purchased equity issued by the corporation in the capital markets. Firms compete for capital and investors compete to purchase common stock. Shareholders select management to run the corporation. Management's directive is to maximize the value of the shareholders'wealth, measured by the price of the firm's common stock. Management accomplishes its goal by using the cash raised in the capital markets to acquire plant and equipment. The firm combines these with materials and labor to produce products and services for sale, and sells its goods and services in competitive product markets. The firm's goal is to maximize cash flows for shareholders. The cash flow returns to the shareholders as dividends and capital appreciation of the firm's stock. The ratio of the cash flow and the shareholders'initial outlay for stock is the rate of return earned on the shareholders'equity. (See chart at left) Management can issue debt as well as equity, in order to bring cash into the firm. If it issues debt, the firm's expected cash flow must be large enough to pay the interest and principal on the debt and still earn the rate of return desired by the shareholders. The firm's required return on investment is the ratio of expected cash flow to the firm's debt and equity, ROI. ROI = Expected Cash Flow Debt + Equity 22 Migration Patterns of the Tampa Bay and the South Central Florida Regions Continued from page 21 The Private CorporationShareholders Management Input MarketsCapital Markets Plant & EquipmentDebt Labor & MaterialsEquity Product Markets Sales Less:Costs Less:T ax es Equals Cash flow ENDNOTES1Migration flow is derived from tax return filings with the Internal Revenue Service. For example, 1997 migration patterns are based on a comparison of the address listed on a taxpayer's 1995 1996 return (filed in 1996 for income earned in 1995) with the address listed on the same taxpayer's 1996 1997 return (filed in 1997 for income earned in 1996).2See "Tampa Bay Region: 2000, ECONOMIC MARKET REPORT," prepared for the Tampa Bay Partnership by the USF Center for Economic Development Research. The Tampa Bay region is defined by the Partnership to encompass Hernando, Hillsborough, Manatee, Pasco, Pinellas, Polk and Sarasota Counties.3Armed Forces Postal Operations / Fleet Postal Operations (APO/FPO) provide mail service for military and certain civilian personnel stationed outside the contiguous US.4See "The Status of South Central Florida's Regional Economy: An Update," May 2001, prepared for the Central Florida Regional Planning Council (CFPRC) by the USF Center for Economic Development Research. The South Central Florida region is defined as the CFRPC service area consisting of DeSoto, Hardee, Highlands, Okeechobee and Polk Counties.5As defined, Polk County is included in both the Tampa Bay region and the South Central Florida region. Redefining Tampa Bay by removing Polk County would decrease the region's net migration, 1997 to 1999, from 118,000 to 104,000 but would only have a negligible effect on the region's annual population growth rate of 1.3%. In like manner, redefining South Central Florida by removing Polk County would decrease that region's net migration, 1997 to 1999, from 15,189 to 1,362 and leave the remaining counties of the South Central Florida region with a miniscule 0.4% annual population growth rate, 1997 to 1999.6The phenomenon strictly holds in 1996-97 and 1997-98, but reverses by a slight margin in 1998-99.
Firms often do not earn their ex ante required return, as events over the production cycle can cause cash flow to differ from expectations. Thus the capital markets determine ROI by the perceived riskiness of the firm's business. Economic Efficiency of Private Corporations. Why do economists argue that private corporations are efficient? They so argue because, at every step of the production cycle, management faces competition. Management must compete for its workers, its plant and equipment, and its intermediate goods in the factor markets. It must compete with other firms to sell its goods in the product markets. And it must compete in the capital markets to issue its debt and equity securities and bring capital into the firm. Shareholder ownership gives the firm a clear objective to shoot at: The firm must maximize the value of its common stock. This mandate drives the rest of management's activities as competition forces it to produce quality products at prices that will sell in the market. Electric Utilities Have Lacked Competition in theirRegional Product Markets. So, we can give three cheers for competitive markets. But, the situation facing electric utilities is not the same as the situation facing other, competitive, industries. In the past, electric utilities have not faced competition in their product market, that is, in the market for generated electricity. The lack of competitive pressure has been due to the nature of the product generatedelectricity, and the way that electricity has been distributedthrough power lines. In the past the average cost per megawatt hour of electric power generation declined as the size of the power plant increased. Because utilities sold the power generated within a relatively small region, there was insufficient scope for many plants large enough to produce at a low unit cost of electricity. Asingle company could supply regional electric power needs with a small number of generating facilities. Electric utilities distributed the power across power lines connected with the generating facilities. Since customers require only one set of power lines, a single regional power company supplier was able to serve all customers in a region. The region might be a city, a set of counties, or an area as large as one or more states. In the past, then, power generation and the regional system of power lines and connecting facilities mitigated towards a single supplier. The breakdown of competition in the product market creates a "natural monopoly" in the region. Shareholders in a monopoly, in order to boost their stock prices, can require management to restrict supply and thus push up the price of the product. Regulation of Electric Utilities. Realizing that unchecked regional electric companies had the incentive and ability to overcharge customers, states and municipalities created regulatory agencies whose roles were to set the prices regional electric companies charged for electricity. Regulators set the price of electricity by formulas that relate cash flow to the capital invested by power companies. They established electricity prices that allowed electric utilities to earn, a publicly set "rate of return" that was calculated using the ratio of cash flow to invested capital ( ROI above). Thus, regulators determined prices that electric utilities were allowed to charge customers. Electric utilities accepted regulated prices in return for an exclusive franchise for their service areas. The Decline in Monopoly Power. Two sets of recent developments have changed the technology of power generation, reducing the degree of natural monopoly enjoyed by electric utilities. The first of these has been the extension of regional "power grids"networks of power transmission lines that cover wide areas of the country. The grid grew as regional power companies connected to the grid. Now the grid can transmit power over wide areas. Indeed, it is now possible to deliver generating capacity produced in one region of the country to consumers in neighboring regions. Power companies have been able to purchase and sell electricity to one another over the grid. Asecond set of technological innovations has centered around the generation of electric power. It is now possible to produce electric power efficiently using more compact power plants. Generation by natural gas provides clean power at a relatively low cost. Natural gas prices were at low levels until recently, when they were impacted by increases in the price of oil. Smaller electricity producers have been able to access the grid and transmit power across it. Companies in mining and manufacturing have constructed co-generation plants to power their own operations, selling the power they don't need to regional electric companies. Companies producing power from alternative sources, such as windmills, have also connected to the grid. In summary an element of natural monopolythe scale economy of generation of electricityhas been eroded by the formation of a power grid and through a decrease in the magnitude of economies of scale in power generation. The final element of the natural monopoly, the network of transmission lines that are used to distribute power to retail customers, remains in place. Electric utilities remain responsible for the transmission lines connecting regional customers with the power grid. The Economics of Electricity Deregulation. States and localities have realized that the ability of local power producers to sell electricity to the grid, and to purchase power through the grid from suppliers in other regions, establishes the precondition for the competitive supply of electricity. Competition can force producers to set prices that reflect generating costs. The most important contribution of deregulation is that it breaks the regulatory link between the utility's capital investment and the cash flow it earns from its business operations. After deregulation, the return on investment to wholesale electricity generation will be determined by the willingness of the capital Continued on page 2423
24 Electricity Deregulation:Part I:A Primer Continued from page 23 market to supply funds to electricity producers on the basis of their future earnings. Utilities will compete with other industries for capital based upon risk and expected return. However, as noted above, one element of the natural monopoly remainselectric utilities still must create and maintain the system of power lines that connects regional customers to generating capacity. The challenge facing regulators is to deregulate electricity prices while insuring that there is some provider that retains the incentive to maintain the regional power grid and its connections to consumers. Eventually, other sources of electric power, such as photo-voltaic cells, solar panels and wind power may allow individual consumers to produce their own electricity, eliminating the need for transmission facilities. That time, however, has not arrived. It is likely, therefore, that consumers will continue to pay a fee to a supplier for their connections to the power grid, and that that fee will be government-regulated. Power generators are linked to consumers through a regional power chain. For competition to prevail the chain must connect power producers and consumers through the power grid. The regional power chain is pictured below: Broadly conceived, the power chain in a region consists of hook-ups with power plants, trunk lines for transmitting power throughout the region (the power grid), and hook-ups with power service providers (PSPs) serving final customers. Deregulation, and innovations in the current regulatory system, must deal with one or more of the four entities in the power chain. If an entity has sole control over one or more of the three elements of the power chain, it retains potential monopoly power. Any deregulation process should separate power generation and power transmission. If the state government does not foresee the certainty of competitive power generation, it should not elect to deregulate the industry at all. If competitive power generation is a reality, transmission still must be dealt with in a regulatory environment. Financing and operating the power grid and the PSPs, therefore, is central to the success of deregulation. Deregulators should keep in mind that the goal of deregulation is to pass the benefits of competition in the generation of electric power on to the consumer. As long as this goal is pursued in concert with market forces rather than in opposition to them, deregulation should be a success. One method of controlling the price of power transmission is to designate the RTO as a regulated monopoly, and to designate one or more regulated monopolies to be the power service providers (PSPs) for electricity customers in a state or region. The prices of transmission are regulated, not market determined. The RTO purchases power from competitive power generators and sells to the PSPs who in turn deliver the power to customers. Consumers pay market prices for the generated kilowatt hours, plus a fixed surcharge determined by a formula that is designed to give the RTO and the PSPs a reasonable rate of return to cover operations and return on capital investment. Customers benefit from a competitively determined price of electricity in the wholesale market, but are subject to volatility in the price of generated electricity. However, this volatility may be mitigated through long-term contracts between the wholesale producers of electricity and the regulated RTO and PSPthat deliver electric current to the retail customers. This partial deregulation strategy has been followed in Pennsylvania. Pennsylvania placed six-year caps on transmission charges, but has not set low caps on retail prices, which would discourage new entrants into the market. One hundred thirty companies supply generated power in the state, and 600,000 customers have switched suppliers. Utilities are free to contract for electricity on a spot and a forward basis. Pennsylvania, by allowing market mechanisms to work, has avoided the rigidity that prevented California's power industry from adapting to increases in oil and gas prices. Another strategy deregulates power generation and franchises the regional transmission network to the highest bidder, much in the same way that television cable companies are franchised. The government entity sets a price for transmission and the sells the right to operate the system for a specified period of time. Franchise fees are in some manner rebated to the residents of the region. The franchise method has the advantage of allowing financial markets to allocate the resources in terms of riskadjusted expected returns, the way the market allocates other resources. Adrawback is that, with a limited time horizon, the franchisee may lack incentive to invest in expansion of the transmission network. (Traditional regulated electric monopolies viewed a new facility as a long-term customer and often extended power connections as a capital investment. The franchisee, with a possibly shorter investment period, might not do so.) Opponents of sprawl might not see this as a drawback, however, preferring that new developers should pay the full costs for new improvements. The Regional Power Chain
used by the California Power Exchange to accept spot bids by suppliers (which set prices according to the highest accepted bid) and because of the perceived risk of supplying power to financially strapped utilities. Asignificant portion of power in California is generated by publicly owned and managed electric utilities. Ironically, municipal utilities were not forced to sell off their generating capacity, and have in fact profiteered by selling excess power through the California Power Exchange to the Southern California Edison and Pacific Gas & Electric at many times their own generating cost. Furthermore, the state public utility commission prevented private electricity utilities from entering into forward contracts (whereby the risk of rising electric prices could have been hedged) with power companies. Rising costs and static prices have squeezed cash flow. Operating at a loss, utilities faced the possibility of forced bankruptcy. Utilities have appealed for relief. As a short run solution, California's Governor Gray Davis has called on the state to use tax dollars to assist the state's utilities. As costs to the state mounted, he authorized an increase in the prices paid by electricity consumers. Thus, the political dance of death between environmental groups, political representatives, regulatory agencies, and electricity suppliers ultimately resulted in inefficient production whose higher costs ultimately are being borne, and will be borne, by firms and residents as taxpayers and consumers. It's the same old story. The responsibility for California's current electricity crisis falls squarely upon the shoulders of State government and the groups who lobbied for current policies. As a long run way out of current difficulties Governor Davis has suggested that the State of California, or its regional governments, might operate electric utilities as public enterprises. (See the following article: How Florida should Structure Electricity Deregulation in the Coming Decade. ) In 1996 the State of California changed the system of controls that regulated the State's electric utility industry. The result has been referred to as deregulation, but the industry has in reality been subjected to a new regime of regulations. The results have been severe disruption in supply, large fluctuations in the price of electricity in the state, and the defunding of the State's two major investor owned utilities; Pacific Gas & Electric and Southern California Edison. What has gone wrong? The answer is that California has provided a classic example of regulatory mismanagement. Some of the problems have little to do with deregulation at all, and others have to do with the new system of regulations imposed upon the industry. The results have been shortages in available power, financial woes for utilities, and the need for renewed State intervention. The problems originated a decade ago in disruptions in the supply of new plant and equipmentgenerating capacityin California. Disrupting utility operations in its input markets, the state and its municipalities prevented power companies from building new generating facilities. Resistance to new plants was fuelled by concerns about environmental impacts of nuclear power and fossil fuel-powered plants, and by the absence of other inexpensive means of generating electricity. Supply in the state thus failed to keep up with demand at current prices. The State's utilities have been forced to purchase power from other states to meet steadily rising demand. The second problem affected the utilities'power generation. State legislators in 1997 unanimously passed assembly bill 1890. The bill contained, among other provisions, one that severed the connection between California utilities'markets for inputs (coal, oil, and natural gas) and their markets for products. The bill reduced retail electric rates by 10% and capped the amount for up to six years. The legislation at the same time required private utilities to sell off their generating capacity to wholesalers and placed their transmission facilities under the control of an independent regional transmission operator (RTO). At the same time, the wholesale price of electricity was deregulated and routed through a trading entity referred to as the California Power Exchange. Private utilities paid the spot price for electricity supplied through the Exchange by utilities located in other states. Electricity deregulation was popular with the state electorate because consumers were protected from market-based price increases but stood to gain if power prices fell. And the trend prior to 1999 had been for generating costs to decline. Rapidly increasing prices of fossil fuels and increasing demand instead drove the price of electricity up because California utilities experienced rising costs of power generation. The cost of alternative electric power (the State linked prices for alternative supplies to the cost of natural gas) and out-of-state electricity rose as well. The price of generated power rose even higher because of the formula 25 Part II: Regulatory Restructuring in California
Part III: How Florida Should Structure Electricity Deregulation in the Coming DecadeFlorida's electric industry is a mix of 32 municipal utilities, electric cooperatives belonging to the Florida Electric Cooperative Association, and 5 investor owned utilities: Florida Power & Light Utility Florida Power Corporation Florida Public Utilities Tampa Electric Company Gulf Power Corporation Some of the investor owned companies are subsidiaries of companies that also own independent generating companies in the state. Proposals forChange. Florida has taken steps to address the new technical realities in its electric energy market. Legislative acts passed in 1978 and 1992 accommodated the formation of a wholesale market for electricity. The Federal Energy Regulatory Commission in 1999 issued Order No. 2000, which encourages utilities to transfer control of transmission facilities to regional transmission organizations. Florida's electric industry is working to create an independent regional transmission organization that will own or lease Florida's transmission system. However, the market remains inaccessible to power companies that do not serve retail customers. On October 9, 2000 the Florida Energy 2020 Study Commission released its work plan. The commission is charged to "determine what Florida's electric energy needs will be over the next 20 years and how best to supply those needs in an efficient, affordable, and reliable manner, while ensuring adequate electric reserves." The Commission is tasked with evaluating options for restructuring Florida's electric power industry. The board plans to have final recommendations during the third quarter of 2001. Aproposal of January 26, 2001 before the Commission suggests a new structure for the state's power industry that has features in common with California and Pennsylvania. Under the proposal, electric utilities would be required to divest themselves of generating plants. Facilities could be sold to company affiliates or to independent generating companies. Generating companies would compete in a competitive wholesale market. Utilities'transmission facilities would be either sold to or controlled by an regional transmission organization, or RTO. The remaining assets and operations, referred to in the proposal as a "load-serving utility", would be a marketing and delivery company that bought power on the wholesale market. The load serving utility is also referred to in the literature as a power service provider or PSP. We will use this term in the following discussion. Unlike California, its purchasing strategies could include long-term contracts and bilateral contracts as well as spot market purchases. Rates charged to consumers would be subject to regulatory oversight. During a transition period, the price the PSPwould paythe price the generating plant would receivewould be subject to an upward cap, thus protecting the utility and the consumer from large price increases. The proposal does not address long-term retail price determination or the stability of the price of electricity in the long run. The proposal contains a suggestion for a fuel cost adjustment mechanism that would allow increases in fuel costs to flow through to consumers. The proposal recognizes the difficulties being experienced in California. However, in its present form, it is unclear to what extent the proposal would allow the competitive market to dictate wholesale prices. Structural issues to be resolved include: What scope of activities will be retained by the state's electric utilities? Is it prudent to force them to divest all generating capacity, or can wholesale market competition be maintained if the new PSPs retain back-up generating capacity? Will the PSPs own the RTO or will it be transferred to a separate entity? Will the PSPs retain ownership of retail hookups, or will these be transferred to the RTO, so that the PSPs become nothing more than sales and marketing companies? Who is responsible for building new transmission facilities, and how will they be motivated to do so? It also is unclear in the long run how PSPs and the RTO will maintain a spread between their wholesale cost and the retail price. These uncertainties must be resolved if private capital is to respond to deregulation and build new generating and delivery capacity. Florida's Electric Power Industry in the Coming Decade. Expect disruption in the U.S. power industry as states experiment with new market and regulatory systems, and as new technology continues to change the economic relationship between power suppliers and customers. But electricity deregulation does not have to be the debacle that we have witnessed in California. Twenty-four states have initiated processes to deregulate energy production. Recent events in California have caused some of these states to put the process on hold. Ratepayers should hope that, as deregulation proceeds in Florida, policymakers will recognize the role of capital markets financing the industry and will account for economic principles in their plans. There are several economic principles that all sides in Florida's electric power restructuring debate should acknowledge. Following these principles should insure that electricity will not become a drag on the prosperity of the state and its residents. 26
employees of the enterprise from the state. Certainly, public employees unions are some of the most influential unions in the U.S. today. Suppliers, also, may lobby the government for advantageous contracts for the sale of inputs into production. Between them, unions and suppliers generate upward pressure on costs. At the same time, homeowners and other business and consumer groups pressure the government to keep the price of the enterprise's products and services low. The state enterprise is caught between rising costs and static prices. The government is tempted to raise taxes to subsidize the state enterprise. But taxpayers resist the state's attempts to raise taxes. Competition breaks down in all phases of the production cycle, and is replaced by pressure politics. Legislators, under pressure from labor, consumers and taxpayers, often fail to give management clear direction on production and pricing policies. The result is that state enterprises end up with continuing operating losses. Attempts to control costs by foregoing new investment lead to inefficient production and higher long run costs. Thus, the state subsidizes the public entity, costs are high, and prices do not reflect costs. Artificially low prices encourage consumption, leading to increased production and more subsidies. National governments have been tempted to run budget deficits and print money to cover the subsidies of their state enterprises. State governments in the U.S. are prevented from employing these devices. The result of public ownership at the state level is more likely to be reduced services and higher taxes. How not to do it: Public ownership does not appear to be a good solution to California's deregulatory headaches, nor should it be embraced by other states. Principle #2. Don't forget to water your plants. Potential investors in private corporations must expect the returns to new investment to earn a competitive return. Otherwise they will not supply the capital need to create corporation. Principle #2 holds for power generation, regional transmission lines, and lines and equipment supplied to customers. Policymakers must ensure that Florida's electric industry structure allows investors in all stages of production and distribution to expect to earn normal profits on new investment. Power generators, if they are forced to compete with one another, will be unlikely to earn monopoly rents. If competition is ensured, the state should not regulate the price charged for generated electricity. Prices fluctuate as market forces shift. As in other industries, the consumer bears increased costs, and benefits from periods when costs decline. If the supply of competitively produced electricity is regulated, shortages are likely to result. Shortages lead toPrinciple #1. Don't kill the goose that laid the golden egg.In California, Governor Davis'proposed solution-public ownership-would transfer pricing power to a public authority, eliminating the counter-productive disconnection between the retail prices and wholesale prices that currently creates power shortages. Experience from a number of countries over the past half century suggest that a state-run enterprise, over time, accumulates problems which lead to systematic losses and permanent public subsidies to the enterprise. Difficulties with state run enterprises may be summarized in the following figure. The figure is a public enterprise (or, state enterprise) counterpart of the diagram of a private corporation shown in the preceding article, Electricity Deregulation: a Primer. The major difference between the two diagrams is the role of the owners of the company. The public enterprise has no equity owners. The owners of the public enterprise in the following diagram are, at least conceptually, the residents of the state. Residents are also stakeholders in their roles as taxpayers and as consumers of electricity. Unlike shareholders, residents have no direct control over the management of the state enterprise, nor are their fortunes tied directly to its profitability. As taxpayers they are impacted by taxes and, as consumers, by the cost of electricity residents are both "tax investors in" and "consumers of" electricity. Residents, as voters, control the public enterprise through their elected officials, who in turn are responsible for directing the firm's management. Legislators and executive branch officials are not selected solely for their management of the enterprise, however, but on a wide range of issues, including general fiscal policy, income redistribution, and social policy. Unlike managers of private corporations, they have many, often conflicting, goals for the enterprise. The experience with public enterprises in many countries has shown that state ownership multiplies the political pressures that have caused the energy crisis in California. The state, as a political entity and as a monopoly utility, is subject to pressures from special interest groups that seek to influence its management of the utility. Labor unions, shown in the diagram as large political contributors and as a voter bloc, attempt to lever their influence to gain wage and benefit concessions for the Continued on page 28 The State Enterprise "# $ #! #! % &! 27 "#' " % ("Feeling the Heat"
tricity below production costs and exhorted consumers to practice conservation. Authorities bemoaned the fact that most consumers ignored them. Only recently did the state regulators allow increased costs to be passed to consumers. This was after they had obligated taxpayers to buy electricity on behalf of the beleaguered utilities. Principle #4. Long term contracting. Electric power cannot be stored economically: It must be used when it is produced. This characteristic can make budgeting for electricity costs for consumers and producers difficult. Long term contracts and forward contracts are methods of reducing uncertainty and smoothing expenditures over time. Under a long-term contract, generators and customers (independently or through their PSPs) can agree on an average price for a specified future period. Investors are surer of earning a required rate of return (ROI), and consumers have a better handle on the size of their future electric bill. How not to do it: In California, fearing utilities would enter into sweetheart deals that limited competition, regulators forced utilities to buy all their power on a newly created exchange on which electricity was traded at spot market prices. Principle #5. Be bold! Be bold! Be not too bold!. (The kiss principle) While Florida's restructuring of its electric power industry should be in harmony with economic principles, it is not wise to develop complicated but untested structures that are based upon theory not appropriate to the specific situation, and to foist them on the public. Humility is in order because it is not usually possible to foresee all the consequences of regulatory or fiscal actions by government. There is much history of well-intended policy initiatives that, through the "law of unintended consequences", have led to costly misallocation of resources. Florida's best bet for regulatory restructuring is to articulate clear goals for a revamped electric power industry that incorporates input from existing providers as well as state and local regulatory bodies. The structure should specify the following: Who will be permitted to participate in electric power generation, and under what conditions? Conditions include capitalization, regulatory review, access to the power grid, and recovery of stranded costs. Given the uncertainties facing the industry, price caps may be introduced, contingent upon the emergence of monopoly power. Price caps should be high enough to encourage entry into the market. Ownership and control of the RTO. (Including who shall own the RTO. The RTO may be a cooperative or a corporation.) How will reimbursement for valued added by the RTO be determined? How will value added by PSPs be determined? How will monopsony power (control of the price of power by a single PSPin a region of the state) be regulated?28 Part III:How Florida Should Structure Electricity Deregulation in the Coming Decade Continued from page 27 restrictions in supply, which result in power outages. Power outages are much more costly than temporary spikes in the price of electricity. If price rises above the long-term cost of supply for any period of time, suppliers will add capacity and return the price to its longer-term equilibrium level. The overriding consideration for power generating companies is that competition be assuredthat all power suppliers have equal access to the RTO and, via the PSPs, to the final consumer. Policymakers in California were concerned that, if allowed to operate generating facilities, utilities would limit competition from other power generators. Fearing this outcome they forced electric utilities to divest their generating facilities. PSPs should be encouraged to retain some generating capacity, however, because they are responsible for ensuring uninterrupted service to customers. PSPs can utilize owned generating capacity to plan for uninterrupted service. The RTO and the PSPs do not face competition for customers. These entities should be subject to a regulated price that allows for an expected return sufficient to stimulate new investment as population and business activity rise. Once the state has established a regime for insuring adequate returns to new investment, it must allow the development of new capacity as demand requires. A transparent and efficient permitting process that allocates land for generating capacity and for access to customers, and streamlined environmental and impact regulations are critical if a supply of electric power is to be assured. The public must be protected from environmental degradation. The regulatory process should require suppliers to bear the full costs of environmental regulation. Suppliers in turn must be allowed to pass those costs to consumers. On the other hand, opponents must not be given scope to block the development of properly regulated generating plants, transmission wires, and customer service facilities. How not to do it: No significant new power generating capacity has occurred in California for several years, as projects are tied up in expensive litigation. Principle #3. Caveat emptor:Let the Buyer Beware! An element of principle number two is that demand is best served by allowing the price paid by consumers to reflect competitive market conditions, thereby avoiding artificially created shortages. This principle extends to the pricing of electricity across periods of peak and slack demand. The cost of a kilowatt of electricity during periods of peak demand may be several times that of a kilowatt generated in the middle of the night. Current technology allows producers to vary the price according to cost of generation and transmission. It also enables consumers to be notified of the cost of power on a continuous basis. Consumers typically respond to price differentials by shifting a portion of their power usage from peak hours to slack hours, and by cutting consumption during days or weeks when the price is high. How not to do it: California long kept the cost of elec-
The Economic and Statistics Administration documents and explains economic and social change through demographic and economic statistics. The ESAincludes both the Bureau of Economic Analysis and the Census Bureau The International Trade Administration includes the Import Administration the Trade Development Center the Office of Market Access and Compliance the U.S. Foreign and Commercial Service and the Trade Information Center The Import Administration enforces laws and agreements to prevent unfairly traded imports and to safeguard jobs and the competitive strength of American industry. The Trade Development Center is U.S. industry's link to global markets, working to promote U.S. exports. The Office of Market Access and Compliance's paramount objectives are to obtain market access for American firms and workers and to achieve full compliance by foreign nations with trade agreements they sign with our country. The U.S. Foreign and Commercial Service places primary emphasis on the promotion of exports of goods and services from the United States, particularly by small businesses and medium-sized businesses, and on the protection of United States business interests abroad. The Trade Information Center is a comprehensive resource for information on all U.S. Federal Government export assistance programs. Among all of these offices, data collection is primarily the responsibility of the U.S. Census Bureau. The U.S. International Trade in Goods and Services Report, commonly referred to as the FT900, is required by law to be published on a monthly and cumulative basis by the Census Bureau. The FT900 includes national-level data on imports International Trade Data: What is Available and What Does it Mean?By Gina B. Space,Economist with the Center for Economic Development Research The U.S. Government collects abundant data on economic activity in the United States and is a primary source of international trade data. Much data is available by the location of economic activities and the destination of products. Source and destination data allow the researcher to estimate the value of commerce that flows across our national borders. However, because of regulations on government disclosure, locating and obtaining data specific to a state, sub-state region or industry or product code is not always possible. Confusion also arises because multiple federal agencies collect and disseminate international trade data. Among these agencies are several divisions within the Department of Commerce (see below); the Customs Service, housed within the Department of the Treasury; the International Trade Commission; and the Department of State. In addition to collecting data on the trading entity and its products, federal agencies and offices license exporters, calculate and collect duties, enforce quotas, conduct research on markets and industries, and connect U.S. businesses with likely trading partners in other countries. These offices also administer many other programs and issue and enforce rules and regulations relating to the shipment of goods across our international border. Within the Department of Commerce, the Bureau of Export Administration, the Economic and Statistics Administration, and the International Trade Administration all have responsibilities relating to international trade. Within those three Administrations, there are additional distinct offices with different missions and services. Each administration's or office's mission is defined below: The Bureau of Export Administration regulates the export of critical goods and technologies that could be used to threaten U.S. national security, foreign policy or economic interests.29 What pricing mechanisms will be in place? Aspot market for electricity must operate, but firms and consumer should be able to hedge against cost and demand fluctuations using long term contracts or electricity futures. Atimetable should be adhered to as closely as possible. Undoubtedly there will be changes in the regulatory structure and in industry structure as the system goes into operation. However, rules and timetables should be adhered to as much as possible to allow all actors in the process to form expectations and to plan operations. Uncertainty will retard investment and restrict supply, leading to more costly electricity. Investors should be assured that, should changes be necessary, the State will cooperate with firms to help them avoid losses arising solely from changes in the regulatory process, but not from natural market conditions. Users should be assured that they will be protected from unforeseen price spikes that result in large windfall gains to producers and that result solely from the regulatory process and not from natural market conditions. How not to do it: In California, the competitive spot market established to price electricity controlled all power supplied to privately owned public utilities but failed to involve municipal utilities. On the other hand, the price utilities could charge for power was capped. This untested market structure failed to perform adequately when subjected to increased costs of power generation. Continued on page 30
International Trade Data:What is Available and What Does it Mean? Continued from page 29 of Trade and Economic Analysis, International Trade Administration, Department of Commerce, publishes metro area level merchandise exports to selected destinations based on the ELseries. However, not all metro areas are reported due to disclosure regulations. And although data are reported for each world region total, only selected countries are listed separately from those totals. Specific sub-state trade data classified by industry or SIC and country of destination is not available to the public. While the exporter of record is not necessarily in the same location as the producer of the export good, there are still many instances in which the two coincide. In fact, the Census Bureau estimates that for manufacturing firms which export, the location of production and the exporter of record are in the same zip code 88 percent of the time, as measured by the value of goods exported. In addition, the ELseries can be used to estimate export production in a locale when: there are few intermediary exporters; manufacturers are especially prominent exporters; the region is known to produce the goods being exported; and the value in the ELseries is close to the value in the Origin of Movement series. The Origin of Movement (OM) series, which has been collected since 1987, assigns the value of exports to the original location from which the final product was shipped to the port of exit (referred to as the "point of origin" ). The OM series was designed to assist transportation planners and providers in developing the infrastructure necessary to move goods from within the United States to ports of exit. Many consider the OM series a better predictor of the location of production, but the series is also limited. First, the OM series is a state-based series. The information requested during data collection is the state of origin, not the zip code. Therefore the data cannot be attributed to a sub-state level, i.e. a county or region. (However, as discussed above, while the ELseries is collected at the substate level, detailed data is not available below the state level.) Instructions for the OM series advise exporters and shippers to attribute the value of products to the "point of origin" as follows: (1) the location of the factory, distributor, regional warehouse or cargo processing facility the state in which the product actually started its journey to the port of export; (2) the state of the commodity which has the greatest dollar value in a multi-product shipment; (3) the "state of consolidation"; or (4) the Foreign Trade Zone from which the product is shipped. Asecond limitation of the OM series stems from inaccurate information supplied by intermediary exporters. The Census Bureau has found that intermediaries provide the state of their location, as opposed to the state where the product began its journey, over 50% of the time for "point of origin" information. Amajority of the remaining intermediaries provide the state in which the port of exit is located, which often times is not the state from which the product was shipped.30 and exports by various categories, such as trade in goods, trade in services, and trade by commodity groupings, by advanced technology products and by motor vehicle parts. At the state level, the Census Bureau publishes two data sets on the value of merchandise exports. (Import data is discussed below.) Export data at the sub-national level covers only trade in goods, or merchandise. Coverage of trade in services is limited to national estimates included in the FT900. The two data sets available are the Exporter Location (EL) series and the Origin of Movement (OM) series. Both the ELand the OM series measure merchandise value on a f.a.s. (free alongside ship) basis. The Exporter Location (EL) series was instituted in 1993 to collect data for the purpose of export promotion The EL data series assigns the value of the goods exported to the zip code in which the exporter of record is located. The exporter of record is technically defined as the "entity which is principally responsible for effecting export from the United States." The exporter of record is essentially the entity which sells the merchandise to a foreign buyer. However, the exporter of record is not necessarily the same as the export producer, nor are the two necessarily in the same location. The exporter of record can vary from the producer or manufacturer of a good for a number of reasons. First, the exporter of record may be a separate division of a company which also produces the good sold. The product may be manufactured by workers at a plant in one state but sold through the international division of the firm, whose headquarters is located in another state. Second, the company may sell its product both at home and abroad. The domestic division may be located in a different state than the international division for various reasons. Third, the exporter of record may be an intermediary or wholesale trader, as is the case with many agricultural commodities. The intermediary exporter may purchase the goods from a producer in one or more states, transport the goods, and then effect the export from another state. (Probably one that has a good shipping port or is close to the final customer.) By design, the ELseries provides information on export activity As a result of assigning the value of exports to the location of the exporter of record, the ELseries cannot be used to approximate the value of export production in a given location. However, firms do use the ELseries to promote and service export activities; i.e. they provide financing, shipping, travel assistance and communications services to the exporter, targeting export industries according to the data. To a large extent, the ELseries can be used by economic development professionals to gauge the level of international commerce, or connectivity, within their district. While the data is collected at the zip code level, only selected sets are available at the sub-state level. State level data by 2-digit Standard Industry Classification (SIC) and by country of destination is available for purchase from the Census Bureau's Foreign Trade Division. The Office
ing tariffs, enforcing quotas, collecting statistical data for policy-makers and adjudicating claims of illegal import activities such as dumping. Because reasons for collecting the data are national in scope, import data is aggregated at the Customs Management Center (CMC, formerly Customs District) with responsibility for oversight of the port where the goods enter the country. Export data is also collected, aggregated and distributed at this level and can supplement the ELand OM series data. (Import/Export data at the port level are available from the Port Import Export Reporting Service (PIERS) on a fee basis.) CMCs are groupings of international ports of entry in a given geographic region. Ports may be airports, seaports or land border crossings, and districts can cross state boundaries. Florida is exclusively and totally encompassed in two CMCs: the North Florida CMC (formerly the Tampa Customs District) and the South Florida CMC (formerly the Miami Customs District). The ports assigned to each CMC are listed in Table 1 (see page 32) and corresponding geographic territories are displayed in Map 1 (below). Data available at the CMC level refer simply to the flow of good through the numerous ports which fall under a given CMC. While such information can give a good picture of the level of total port activity in a CMC, the data describe only the flow of goods and are not indicative of manufacturing, export activity or consumption levels in a CMC. (Once goods enter the country, imports can be shipped to any of the 50 states for consumption without being tracked. Likewise, exported goods can come from any place in the U.S. and the value of those goods will be attributed to the port's CMC.)31 This limitation heavily affects allocation of nonmanufactured exports, especially agricultural commodities, since they are most often marketed and sold through intermediaries. The result is an understatement of export value for states with a large amount of agricultural production and an overstatement of export value for states with ports from which high values of agricultural products are shipped. Using the ELand OM series together can help provide a more complete picture of export production and activity in a given state. The ELseries can show broadly what industries have international connections in a given state. It can also help export promoters focus on strengthening the relationships which are so important in doing business with other countries. Economic development professionals can use this information to connect interrelated industries to common export markets and vice versa. The OM series can help define the export activity of manufacturers within a state. It can identify the industries and businesses in which the state has a global competitive advantage. Additional analysis and comparison of the OM series to the industry structure in a state can highlight particular strengths and advantages which economic developers can use to promote international industries in their states and regions. When the two show similar patterns and values, the EL and OM series are a fairly accurate measure the export activity of a state. Where they differ, other important information can be gleaned. For example, an ELseries that is much greater than the OM series for an industry may indicate the state has a geographic advantage with respect to export activity. That is, it could be that the state and its residents have developed the international relations necessary to facilitate export activities. Alternatively, there may be a higher concentration of wholesalers or intermediaries and therefore good port infrastructure. Conversely, where the OM series exceeds the ELseries, businesses have chosen to ship products to another state for export sales activity. Factors influencing a business'decision to ship out of state include cost, distance, transportation infrastructure and providers, port capacities and amenities, sale through intermediaries, and relationships with service providers and customers. In sum, opportunities to build a stronger position in the international trade community can be discovered by utilizing both series and understanding the differences. While data on merchandise exports are available in the ELand OM series, data on merchandise imports are not available in a completely comparable format. Import data are collected by the U.S. Census Bureau, the Customs Service and the International Trade Commission. The purposes for collecting data on imports include assessing our national accounts and trade balances, imposing and collectContinued on page 32
International Trade Data:What is Available and What Does it Mean? Continued from page 31 An importer or exporter may choose to ship through a port in the North Florida CMC because the cost of transportation is more favorable, the time in shipment is minimized, the business-person has an established relationship with port or customs staff, and for many other reasons. CMC trade data can supplement the ELand OM series and can be very helpful when trying to explain specific changes in metro-level trade patterns, but it is really only a measure of port activity. The limitations of available trade data make it difficult for economic and trade development officials to completely understand the structure of international trade activity within their regions. The lack of trade data at the sub-state level compounds this problem. Without a clear picture of the current level of trade activity, it is difficult to make decisions on investments in infrastructure, programs and policies. Moreover, once decisions are made, it is nearly impossible to measure their results and effectiveness. In order to have a solid trade promotion program, based on actual trade activity, additional trade data with greater industry detail and levels of geography must be collected and released. Without this data, international trade activities will be unnecessarily restricted. NON-PROFIT ORG. U.S.POSTAGE PAID Tampa,FL Permit No.257 )* + ,,-,+ ./0 1/#223-.