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THE EFFECT OF TAXES ON EMPLOYMENT AND POPULATION IN THE WASHINGTON D.C. AREAStephen T. Mark, Therese J. McGuire, and Leslie E. Papke A report prepared for the D.C. Tax Revision Commission Draft: October 24, 1997 CONTENTS
TABLES [Not available on-line] I. INTRODUCTIONAn important part of a comprehensive evaluation of the District's tax structure is to assess the impact of taxes on economic development. A commonly heard criticism is that the District's high tax burden is a deterrent to the location of jobs and people in the District. Other commentators counter that quality-of-life factors are dominant in explaining the relative performance of the District. Still others assert that the fortunes of the District are not discernibly different from other central cities in large metropolitan areas, thus implying that cutting taxes to attract employment and people is not likely to be an effective policy. In this report we bring systematic evidence to bear on these various assertions. In the next section we compare recent trends in employment, population, and income of the District and its metropolitan area to other central cities and metropolitan areas. This comparison enables us to check the validity of the often asserted uniqueness of the District's situation. It also provides a context for the detailed analysis of employment and population in the District and its surrounding suburbs that follows in section III. In section III we investigate various factors as possible determinants of employment and population growth in the District and eight surrounding suburbs in Virginia and Maryland. The study is thus one of the effect of various factors, including taxes, on differences in intra-metropolitan growth rates. Within the limitations of regression analysis, the results speak to the question of whether taxes or the crime rate or any other factor explains the differences in employment and population growth rates observed across the nine jurisdictions in the D.C. metropolitan area. The final section of the report summarizes and interprets our findings. II. A COMPARISON OF WASHINGTON D.C. TO OTHER LARGE CITIES AND THEIR SUBURBSTo place recent economic and demographic changes in the District and its metropolitan area in context, we compare the performance of the District to several other large cities. To do so we have compiled two data sets, one consisting of information on 22 cities and their metropolitan areas and the other consisting of information on seven cities and their surrounding suburbs. The 22-city data set is comprised of the 20 largest cities in 1980, which included Washington D.C. We also add Atlanta and Boston since they are currently similar to the District in size. The seven-city data set contains seven large cities, including the District, that do not have overlying counties. These cities are more comparable to the District than are cities that have overlying counties to provide government services and impose taxes. While the six cities are not perfectly comparable to the District because they have overlying state jurisdictions, the comparison is of interest because the high taxes in D.C. are often times attributed in part to the lack of overlying jurisdictions. The data for the 22-city data set were obtained from the Bureau of Economic Analysis (BEA) (metropolitan areas) and the Bureau of the Census (cities). Because these two sources differ, the data are not perfectly comparable, but we are unaware of any other comprehensive source of data that covers several years for metropolitan areas and their component cities. The seven-city data were obtained from the same BEA source. Since the central cities in these seven metropolitan areas are effectively counties, the BEA data set, which provides data by county, covers them. Below, we use these data to compare population, employment and per capita income growth rates across the District and similar areas. Table 1 presents population growth rates for the 22 cities and their metropolitan areas over the time periods 1970 to 1992 and 1986 to 1992 (1992 is the most recent year available from the Census for cities). The fastest growing metropolitan area over the more than twenty-year period was Phoenix, with growth of 122 percent. During this period three metropolitan areas actually lost population. The average growth rate for the twenty-two areas was 21 percent. The population growth rate of the District metropolitan area at 35 percent exceeded the average. The twenty-two central cities did not fare as well as their metropolitan areas from 1970 to 1992. The average growth rate of the cities was essentially zero compared to the average metropolitan area growth rate of 21 percent. While several central cities, largely cities in the west, experienced rapid population growth, many others lost population including the District which lost nearly 23 percent of its population over the period. Only Cleveland and Detroit lost greater percentages of their populations during this period. It is notable that unlike the District metropolitan area, the Cleveland and Detroit metropolitan areas also lost population over the period. The story is much the same for the recent period from 1986 to 1992. On average the metropolitan areas grew much faster than the central cities, and the District metropolitan area grew faster than average; several central cities, including the District, lost population over the six-year period.
In Table 2 we display employment growth rates for four major industries over the two-decade period 1972 to 1992. While we are limited to these four industries by the coverage of the Census data, in 1995 these four industries represented 77 percent of total private employment in the U.S. Over the two decades the fastest growing industry in these metropolitan areas was services with an average growth of 116 percent. Manufacturing employment actually declined by 15 percent on average. For three industries, manufacturing, wholesale trade, and services, the metropolitan areas outperformed the central cities, but services employment grew slightly faster in the central cities than in the metropolitan areas. Employment growth in the D.C. metropolitan area was greater than the average of the metropolitan areas for each of the four industries, and notably so for manufacturing. In contrast, manufacturing employment declined in the District proper by 33 percent, a percentage amount slightly less than the average decline of the central cities. The District's services employment growth of 125 percent was virtually identical to the average for the cities, while its employment growth rates in the two trade industries were much lower than the averages for the cities.
Table 3 displays real income per capita growth rates over the period 1969 to 1989 for the twenty-two cities and their metropolitan areas, as well as levels of real income per capita for 1989 (and 1994 for the metropolitan areas only). Real income per capita increased nearly 40 percent on average for the metropolitan areas over the twenty-year period, while it increased 26 percent for the central cities. Real income per capita actually fell in the central cities of Cleveland and Detroit. Both the District and its metropolitan area experienced faster than average growth in real income per capita over the period. In 1989 real income per capita was $16,745 on average for the cities, and significantly higher at $23,660 on average for the corresponding metropolitan areas. Both for the District and its metropolitan area, real income per capita was substantially above the corresponding averages, and second only to San Francisco and its metropolitan area (by 1994 the D.C. metropolitan area was third behind the San Francisco and New York City metropolitan areas).
Seven City Growth Rates Compared In Table 4 we present growth rates for several variables for the seven cities and their metropolitan areas over the time periods 1969 to 1994 and 1991 to 1994. Recall, these seven cities are of interest because they have similar intergovernmental arrangements in that their central cities do not have overlying counties. On average over the 25-year time period population declined by 13 percent in the central cities but increased eight percent in the metropolitan areas. The contrast was even starker for the District as the city lost 26 percent of its population over the period while the metropolitan area gained 42 percent. The same relative patterns held during the recent period of 1991 to 1994, a period of general expansion in the economy. On average the city and metropolitan area growth rates of real income per capita were nearly identical for the seven comparison areas, growing over 40 percent over the 25-year period. During this period, which includes the early 1990s, real income per capita grew faster in the District proper than it did in the metropolitan area (a pattern the District shared with St. Louis). It is possible that this could be attributable to middle income flight from the District to its suburbs. Total private employment grew only slightly faster on average for the seven cities than it did in the District from 1969 to 1994. On the other hand, the Washington D.C. metropolitan area experienced significantly more rapid total employment growth than the average of the seven metropolitan areas both over the 25-year time period and in the 1990s. From 1969 to 1994 manufacturing employment declined less in the District compared with the average of the seven central cities. An interesting comparison is between the District and its metropolitan area in contrast with the averages for the seven cities and their suburbs. Manufacturing employment declined significantly for the average of both the cities and the metropolitan areas. In the District, by contrast, while manufacturing employment declined in the city, it grew rapidly in the D.C. metropolitan area. The D.C. metropolitan area performed well relative to the average of the seven metropolitan areas for each of the four industries displayed during both time periods. For the District proper relative to the average of the seven central cities, this is the case only for manufacturing and services and only during the 25-year time period.
In summary, the District and its metropolitan area performed similarly to other comparable cities and metropolitan areas in population growth over the last 20-25 years in that metropolitan area population growth out paced the population growth (in many cases decline) of the central city. With respect to income and employment, the District performance was somewhat different from the average of comparable areas. The growth rate of income per capita over the more than two decade time period was higher in the District proper and its metropolitan area than for the averages of the comparable areas. In terms of employment growth over this period, the D.C. metropolitan area outperformed other metropolitan areas across all industries, while the District proper generally, but not for each industry, performed poorly relative to other central cities. III. INTRA-REGIONAL ECONOMETRIC ANALYSISIn this section, we use regression analysis to determine which factors are the key determinants of population and employment growth in the District and surrounding metropolitan area. Regression analysis is a systematic method of determining whether the measure of interest, say employment growth, is related to a number of possible explanatory factors, such as taxes. By testing all factors at the same time, the method allows each factor to be examined holding all other factors constant. In other words, once all other factors have been controlled for (given the values of all other factors), the method asks, does the factor in question have an additional impact on the variable of interest? This is important, because it is often the case that two variables will be correlated, but the correlation is not valid in that it reflects the effect of another relevant factor that has not been controlled for. The method also provides a measure of the amount of variation in the variable of interest that is explained by the set of factors tested. Employment growth is of interest for obvious economic development reasons. But population or choice of residence has more than the usual implications for economic activity since the District is not allowed to tax non-resident workers. Our geographic area includes the District and eight surrounding counties/cities: Charles, Montgomery, and Prince George's Counties in Maryland, and Alexandria City, Arlington, Fairfax, Loudoun, and Prince William Counties in Virginia. Our data sources are listed in an Appendix. We summarize our major findings below.
Influences on Population Growth Rates We examine the influences on the population growth rate for the District and eight surrounding counties from 1969 to 1994. Over this period, the average annual growth rate in population for all jurisdictions is 1.75 percent, ranging from a minimum of -1.18 percent (District of Columbia) to a maximum of 4.38 percent (Loudoun County, Virginia). We relate the resident population growth rate to three sets of variables. First, we include the tax rates of taxes paid by individuals: the sales tax, the property tax, and the personal income tax on incomes of $25,000. Second, we include: per capita income, a per capita crime index derived from the FBI Uniform Crime Reports, per capita AFDC expenditures, and total per capita local expenditures. Third, we include variables characterizing the industrial composition of employment (the fraction of private employment in manufacturing, for example) because there is some evidence suggesting that different types of employment may influence growth. It is natural to think that population does not respond instantly to changes such as in the income tax rate, so we use the one-year lag of these variables in the regressions. We allow for a flexible annual growth rate for the entire region, and control for aggregate effects that affect either population growth, or the policy and environmental variables. In addition, we include controls for permanent differences across the jurisdictions or qualitative differences that we are unable to measure. Thus, all estimates measure the effect of, say, the personal income tax on population growth rates net of aggregate regional trends over time, and long-term differences between the jurisdictions. Because we include these general controls, in our discussion below we extend the conventional significance level of statistical tests from five percent to fifteen. For example, we consider a variable to have a statistically significant influence on population growth if the estimated coefficient's p-value (the probability of observing that coefficient if the true coefficient is zero) is 0.15 or less. We also report p-values for all coefficients for the interested reader. Our calculation of the local personal income tax rate (on incomes of $25,000) indicates that the District does not stand out as a particularly high personal income tax jurisdiction - the District, and Charles, Montgomery, and Prince George Counties have similar rates. The District does have the highest sales tax rates. In 1994, the last year in our time series, the District rate was an average of 6.69 percent, compared to 4.0 or 4.5 percent elsewhere in the region. (In 1996, the District's sales tax rate was down to 5.75 percent.) The District's property tax rates, while higher in the early years of our panel, have fallen (as the other jurisdictions' have) to be comparable with or below its neighbors. Table 5 reports our results for population growth. Column (1) in Table 5 indicates how each jurisdiction grew on average. While all counties except Loudoun grew more slowly than Prince William (the jurisdiction against which we measured other jurisdictions), the district's growth rate was the slowest, averaging about five percentage points (5.1) less each year. Most (63.18 percent) of the variation in population growth rates is explained by permanent differences between the counties. But, a comparison of the unchanging attributes of the District across each column of Table 5 indicates that once differences in tax rates, environmental and expenditure policy variables, and employment shares are accounted for D.C.'s population growth rate experience no longer stands out. Systematic differences in the explanatory variables explain variations in population growth rates. Column (4) of Table 5 presents the most complete picture. Tax rates do not appear to influence population growth rates in the region. The taxes that are exclusively paid by residents -- the personal income and property tax -- have a negative sign as expected, but the estimates are not statistically significant. The growth rate in population and the tax rates are measured in decimal; a one percentage point increase in the personal income tax rate is predicted to reduce the population growth rate by 0.63 percentage points. A one mill increase in the property tax rate is estimated to reduce the population growth by 0.69 percentage points. Because neither of these has a p-value of 0.15 or less, the effects are not statistically different from zero. A one percentage point higher sales tax, with its potential for export to nonresidents, is estimated to increase the growth rate by 0.79 percentage points, but again, the level of precision does not meet our standard (a p-value of 0.17). We also find that as a group the tax rates have no influence on population growth in this region. Of the environmental variables, per capita income plays a statistically significant role in attracting residents. A ten percent increase in per capita personal income implies a 0.61 percentage point increase in the population growth rate (with a p-value of 0.08). The District's average per capita income places it in the middle of these jurisdictions. The District is a standout in per capita crime, however. The District averages about nine crimes per hundred residents over this period, while most the jurisdictions average about four, except for Alexandria City with 7.7. The crime index, however, is not statistically significant and has a small estimated effect as well. This lack of an effect of the crime index has two possible explanations. First, the crime data from the FBI may be of poor quality so that our crime index may be an inaccurate measure. Second, and more importantly, our evidence indicates that once we control for the other important factors, the crime index does not appear to have an additional, independent effect. Of the expenditure policy variables, per capita AFDC expenditures is estimated to be a statistically significant and negative influence on the growth rate of population. The estimates indicate that a ten percent increase in per capita AFDC expenditures implies a 0.17 percentage point drop in the growth rate (with a p-value of 0.03). We have no measure of poverty rates at the jurisdiction level; but since AFDC expenditures are driven primarily by caseload, this variable may be a proxy for the number of welfare recipients per capita. If so, our results would indicate that concentrations of poverty negatively affect population growth. The District's per capita AFDC expenditures are much higher than in the surrounding counties. We have no proxy for the quality of public services; total expenditures at the jurisdiction level has the wrong sign and is statistically insignificant (with a p-value of 0.74). This is likely to be a measurement error problem due to the political economy of the region. The level of public services (leaving aside quality) is a difficult concept to compare across these jurisdictions, since the District is responsible for a vast array of services, including those that Virginia and Maryland make for the other jurisdictions. The District's per capita total expenditures are far higher than in the surrounding areas. We include the employment shares from major industrial groups to determine if certain industries attract or repel residents. Industrial composition of an area may affect the desirability of a place to live. An increase in the employment share in either the service industry, or retail or wholesale trade (with a corresponding reduction in FIRE employment share), is estimated to reduce the population growth rate. A one percentage point increase in service, retail, or wholesale employment is estimated to reduce the population growth rate by 0.14 (with a p-value of 0.02), 0.17 (with a p-value of 0.06), and 0.28 percentage points (with a p-value of 0.12), respectively. Higher employment shares in manufacturing or in construction do not appear to influence resident population growth. Influences on the Growth Rate of Private Employment In this section, we examine the influences on the growth rate in private employment from 1969 to 1994. Over this period, the average annual growth rate for the region is 4.40 percent, ranging from a minimum of 0.78 percent (District of Columbia) to a maximum of 7.36 percent (Prince William County). In this section, we use models that are similar to those for population growth, but we employ a slightly different set of explanatory variables. We relate the growth rate in private employment to three sets of variables -- tax costs, environmental, and employment composition variables --(again, lagging them one year), but we replace the tax rates faced by individuals with those tax rates or costs that are applicable to business (the sales tax, the property tax, the corporate income tax, the personal property tax, and the average cost of unemployment insurance. With the exception of the personal property tax, District business taxes are highest on average over this period. The District's commercial property tax averaged 1.98 mills, while the next highest average is in Prince William with 1.44 mills. The District franchise tax rate (similar to a state corporate income tax on corporate net income) averages well above the others (9.3 percent compared to 7.0 or 6.0 for the two states). As mentioned above, the District has the highest sales tax rate. The sales tax is a revenue source traditionally used by states more than localities, but the District is heavily dependent on it. The District's average unemployment insurance costs were the highest for the region over this period. Nationally, fewer and fewer states tax business tangible personal property -- many specifically exempt it as an investment incentive. However, all the jurisdictions in this region do use a personal property tax on tangibles. The tax is levied on machinery, equipment, and inventories, and is not particularly high in D.C. The District ranked sixth in a comparison of average rates, and it exempts inventories -- a fact not reflected in our data. Column (1) of Table 6 indicates that the District employment growth rate averaged 6.6 percentage points less than Prince William County (the base jurisdiction used for comparison). About 23 percent of the variation in employment growth rates is explained by permanent differences between the counties. But again, as with population growth, the District's experience is not unique once systematic differences in the explanatory variables are taken into account. The most complete model is presented in column (4) of Table 6. Two businesses taxes, the personal property tax and the sales tax appear to reduce employment growth. The personal property tax is estimated to have statistically significant and large negative effect on employment growth. Our estimate indicates that a one percentage point increase in the tax rate reduces employment growth by 1.76 percentage points (with a p-value of 0.01). The sales tax also has a large negative effect, and is close to meeting our standard for statistical significance. We estimate that a one percentage point increase in the sales tax rate is estimated to reduce the growth rate in employment by 1.92 percentage points (with a p-value of 0.16). The commercial property tax and corporate income tax variables have positive effects on private employment but they are imprecisely measured. A positive effect of the property tax on employment growth is difficult to explain. If high property taxes are correlated with high spending on schools, this result may be picking up an effect of good schools on business location decisions. The positive and statistically insignificant corporate tax coefficient may result from the lack of variation over time in this variable. The corporate tax rate varies only across states, and Maryland and Virginia do not change their rates over this time period. The only variation left to relate to employment levels is the variation over time in the District, and this does not appear to influence employment growth. Higher unemployment insurance costs also reduce employment growth, but the estimated coefficient is not statistically significant. A ten percent increase in the average cost of unemployment insurance reduces employment growth by 0.17 percentage points (with a p-value of 0.25). Two environmental variables play a role in employment growth. There is some evidence that total per capita income may have a positive effect on employment growth. A ten percent increase in per capita income is estimated to increase private employment growth by 0.94 percentage points (with a p-value of 0.26). While public expenditures did not appear to play a role in population changes, they appear to influence private employment growth rates -- a ten percent increase is predicted to increase employment growth by .33 percentage points (with a p-value of .14). However, the remaining environmental variable, the per capita crime rate, does not appear to influence employment growth. Higher existing employment shares in construction appear to increase employment growth while wholesale trade appears to reduce it. A one percentage point increase in construction share is associated with an increase in total private employment of 0.46 percentage points (with a p-value of 0.08) while a one percentage point increase in wholesale trade share reduces the total employment growth rate by 0.63 percentage points (with a p-value of 0.16). Influences on Employment Growth by Sector To paint a more detailed picture of how taxes affect local economic performance in the DC metro area, we analyze the sensitivity of employment in a number of different industrial sectors. The regressions employ an array of explanatory variables similar to those used to explain total private employment. We focus our discussion on the role of taxes for four broadly defined industries and on the influence of industrial revenue bonds for the subsector of health services. Services and retail trade are the two industrial sectors with the most employees in the District. They represent 66% and 11% respectively of the workers employed by private industry in the District. We also analyze employment in construction because the regressions for total private employment indicate that the share of construction jobs in a jurisdiction may be a significant predictor of employment growth. Manufacturing is included here because of the impressive growth this sector has experienced in the metropolitan area. We think it is notable that the decline in the District's manufacturing sector has been slower than the average major city. In 1994, 75% of manufacturing jobs in the District were in the subsector printing and publishing. Health services comprise over 22% of the employment in services and 15% of total private employment in the District. This is one of the few sectors in which the number of District jobs has increased. In fact, the growth of this subsector in the District has out paced its growth in the metropolitan area. As the District also has an active industrial revenue bond program (IRB) targeted to this industry we test whether the issuance of health related IRBs has an effect on employment growth in health services. Service Sector As in the total private employment regressions, the sales tax is negatively related to growth in the service sector, but in the service sector the effect is more than twice as large (see column 1 of Table 7). The estimate indicates that a one percentage point increase in the sales tax rate reduces the employment growth rate by 4.9 percentage points (with a p-value of 0.01). The service sector is apparently especially sensitive to the sales tax. Finding a strong sales tax effect on this huge sector of the economy reinforces the finding for total private employment. The other taxes shown exhibit smaller effects on services employment growth, and these effects are not statistically significant. Health Services Many of the institutions that comprise the health services sector are hospitals which are specifically exempted from local taxation. We thus omit business tax rates from our health services regression. We include industrial revenue bond (IRB) issuances that are targeted to health related institutions. The issuance information for these bonds is only available for the District, Alexandria, and the Virginia counties. IRBs are measured in thousands of dollars per capita. Four years of health IRB issuances are included in the regression displayed in column (3) of Table 7. Statistical tests indicate that the IRB policy does play a role in attracting health services employment. Including four IRB variables in the regression increases the percentage of the variation explained from 41 percent to 49 percent. Three year old issuances have a statistically significant effect, indicating that three years after the issuance of industrial revenue bonds of $100 per capita, an increase in the growth rate of 4.1% would be predicted. On average the District has issued about $75 million of health related IRBs, or about $135 per capita. Our regression results suggest this accounts for about 60 percentage points of the 125% growth in health services employment between 1985, the inception of the District's IRB program, and 1994. Retail Sector The retail sector accounted for 51,161 jobs in the District in 1994. The results, displayed in column (2) of Table 7, indicate that the sales tax and the personal property tax have highly significant effects, both negative. For example, a one percentage point decrease in the sales tax rate is predicted to produce a 4.0 percentage point increase in the growth of the retail sector in the following year. The p-value associated with this variable is 0.03. A one percentage point decline in the personal property tax rate is predicted to boost the growth rate of retail employment 2.6%. The p-value for this effect is 0.01. The other tax rates have smaller effects and are not statistically significant. Manufacturing Sector As displayed in column (4) of Table 7 the business tax rates do not seem to have a statistically significant impact on growth in the manufacturing sector. A one percentage point decline in the sales tax rate is predicted to yield an increase in the growth rate of manufacturing of 5.3 percentage points, but with a p-value of 0.24, the estimate is unreliable. The effects of the other taxes are also not statistically significant. Construction Sector Of the tax variables only the personal property tax is significant. The negative coefficient of -6.3 on the personal property tax rate suggests a one percentage point drop in the tax rate imposed in a local county or city would yield a 6.3 percentage point increase in the growth rate of construction jobs. Limitations of Our Econometric Analysis Our conclusions regarding influences of policy variables on economic development in the District and surrounding area must be qualified by the limitations of our data. We have used publicly available tax information, but with the exception of Industrial Revenue Bond issues, we have not controlled for the various incentives that jurisdictions offer to business, either as a matter of course, or through individual negotiations. Further, in addition to crime, primary concerns in the District area include quality of education services, and quality of infrastructure. Limitations in school expenditure data reduced the sample size in our regressions to the point that we considered the results to be unrepresentative of the area. We could find no reliable measures of public infrastructure quality to use. IV. SUMMARY AND INTERPRETATION OF OUR FINDINGSWith respect to population growth over the last 20-25 years the District and its metropolitan area looked quite similar to other comparable cities and metropolitan areas. Like other areas, District metropolitan area population growth out paced the population growth (in many cases decline) of its central city. With respect to income and employment, the District performance was somewhat different from the average of comparable areas. The growth rate of income per capita over the more than two decade time period was higher in the District proper and its metropolitan area than for the averages of other areas. In terms of employment growth over this period, the D.C. metropolitan area outperformed other metropolitan areas across all industries, while the District generally, but not for each industry, performed poorly relative to other central cities. In our econometric analysis, we find that taxes paid by individuals do not influence population growth (choice of residence), but that two business taxes, the personal property tax and the sales tax, have statistically significant and large negative effects on employment growth. These two taxes also appear to influence employment growth in the services sector (sales tax only), the retail trade sector, and construction (personal property tax only). Higher per capita incomes attract both population and employment, and population growth is reduced by concentrations of poverty (as proxied for by per capita AFDC expenditures). Higher public expenditures do not affect population growth, but they do increase employment growth. Higher crime rates do not affect either population or employment growth. Both population and employment growth are sensitive to the existing composition of industry. We are able to explain much about the District's experience with population and employment growth with systematic differences in tax rates, environment and quality of life variables. The District is not special -- another jurisdiction with its same tax rates and environmental qualities would have a similar experience. The question is, are these explanatory variables under the control of policy makers? There appears to be little direct action policy makers can take to influence population growth. Our evidence suggests that residence choice is attracted primarily by higher per capita incomes and lower concentrations of poverty. Of course, these characteristics are influenced by the availability of higher-paying jobs, programs that increase employability, and other measures that raise incomes. The District has a high fraction of service employment (66 percent). Policy makers may want to take measures to increase employment in other sectors. Our analysis indicates that employment growth in the region is sensitive to the level of the sales tax and personal property tax. Reducing the sales tax rate (currently highest in the area) or the tax rate on personal property by one percentage point is predicted to increase employment growth by almost two percentage points. Employment growth may also be encouraged by higher local public expenditures, although our conclusions are tentative here. |
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