Ernest P. Goss

The Effect of State and Local Taxes on Economic Development: A Meta-Analysis

Economists and policy makers have long questioned the effect of state and local taxes on economic development. According to Schmenner [55], economists have long argued that taxes had little impact on business location decisions, while development practitioners and elected officials ignored this advice and aggressively pursued development by using tax incentives. More recent research using improved data and methodologies has begun to show that taxes can make a difference, and the emerging consensus among economists now says that taxes do matter. This changing view among researchers is perhaps best exemplified in a 1991 study by Timothy J. Bartik [2]. Bartik examined 84 econometric studies completed since 1979 which assess the impact of state and local taxes on economic growth in the U.S. He concluded that the long run elasticity of business activity with respect to state and local taxes was between -.10 and -.60 for studies focusing on intermetropolitan or interstate business economic activity and between -1.0 and -3.0 for intrametropolitan areas. However, Bartiks study did not control for a variety of study characteristics that may have influenced the measured elasticity. This study builds upon Bartiks analysis by performing a meta-analysis of the studies Bartik reviewed. Meta-analysis is a method for statistically analyzing results across empirical studies. Though it has been little used by economists, researchers in psychology, education, and health sciences have used meta-analysis extensively. This study uses a meta-analytic technique suggested by Stanley and Jarrell [57] to analyze the studies reviewed by Bartik. The technique yields increased precision for our understanding of the relationship between state and local taxes and economic development. The objective of this study is two-fold: first, to derive a more precise estimate of the tax elasticity and, second, to determine how the inclusion and omission of key variables in the estimated equations influences the elasticity estimates.

Do Business Tax Incentives Contribute to a Divergence in Economic Growth

A lack of detailed data on state tax incentive programs has limited the assessment of their economic impacts. However, in 1987, the Nebraska legislature, as part of its new business tax incentive initiative, required that the state Department of Revenue collect data on all business tax incentive agreements and report findings yearly. Nebraska’s legislative mandate produced a unique data set for assessing the impact of a business tax incentive program. Using these data, this article evaluates business tax incentives across Nebraska’s 93 counties during 1987 to 1995 and concludes that qualifying business investment (a) had a positive and statistically significant impact on economic growth for low-unemployment counties, (b) had no statistically significant impact on economic growth for high-unemployment counties, and (c) tended to be undertaken in areas with historically higher investment activity, thus contributing to greater economic performance differences among counties in the state.

The Effect of State Economic Development Agency Spending on State Income and Employment Growth

This study investigates the effect of state economic development (ED) agency spending on state income and employment growth using data from the 1986-1994 period. The study finds that ED spending has a modest positive effect on the generation of state income and employment, even after controlling for the negative effect of collecting taxes to fund ED spending. It is estimated that a doubling of state ED spending (on average

The Impact of Tax Incentives: Do Initial Economic Conditions Matter?

71.5 million in 1992)funded by an increase in taxes would raise the yearly average employment growth rate by 0.16% (from 1.52% to 1.68%) and the yearly average per capita income growth rate by 0.22% (from 4.07% to 4.29%). The study also finds that ED spending interacts with state and local taxes, so that the negative effect of taxes on economic growth is underestimated when ED spending is omitted from the analysis.

Comparing classification accuracy of neural networks, binary logit regression and discriminant analysis for insolvency prediction of life insurers

Do the returns to business tax incentives differ according to the initial economic conditions of the area providing tax relief? Past research studies have provided conflicting answers to this question. Bartik (1991) concluded that rates of return to business tax incentives are likely to be greater for less affluent areas than for wealthier areas offering equivalent incentives. In contrast, Fisher and Peters (1998) determined that tax incentives tend only to offset higher taxes on businesses located in low income areas. This study examines this issue using a unique data set that allows for a fresh look at this issue. We find that the returns to subsidized investment are greater in lower unemployment and higher income areas. This suggests that tax incentives reinforce pre-existing economic differences across areas. Copyright 2001 Gatton College of Business and Economics, University of Kentucky.

Improving health care organizational management through neural network learning.

Past studies have documented the failure of the Insurance Regulatory Information System (IRIS) to provide adequate warning of insurer financial distress or insolvency. As a result, scholars have examined alternative parametric and non-parametric models to predict insurer insolvency. This study uses a neural network, a non-parametric alternative to past techniques, and shows how this methodology predicts insurer insolvency more effectively than parametric models.

Survival Prediction in the Intensive Care Unit: a Comparison of Neural Networks and Binary Logit Regression

In order to provide more ethical and objective measures of the likelihood of Intensive Care Unit (ICU) recovery, hospitals have turned increasingly to decision support system software packages, such as APACHE. However, these packages derive estimates from parametric techniques, such as Binary Logit Regression (BLR) in the APACHE case, and require the developer to specify in advance the functional relationships among variables in the model. Recent rapid advancements in computer software and hardware technology have encouraged researchers to use more computationally intensive, non-parametric techniques such as Neural Networks (NNs), which are purported to be better than parametric models in terms of prediction capabilities. The present study applies both methodologies to a sample of ICU patients and shows that the NN technique predicts mortality rates more correctly than BLR, and offers a promising non-parametric alternative to the parametric methodologies in hospital settings.

The effects of foreign capital on state economic growth

Abstract As a component of hospital cost containment policy, the National Institutes for Health recommends that hospitals limit intensive care unit (ICU) resources to patients who have a reasonable probability of recovery. In order to provide more ethical and objective measures of the likelihood of ICU recovery, hospitals have turned increasingly to decision support software such as APACHE (acute physiology and chronic health evaluation), which derives predictions from binary logit regression (BLR), a parametric estimation technique. Rapid advancements in computer software and hardware technology have encouraged researchers to use more computationally intensive non-parametric techniques such as neural networks (NNs) whose prediction capabilities are purported to be greater than those of parametric models. The present study applies this methodology to a sample of ICU patients and shows that neural networks appear to more correctly predict survival than does BLR.

Women and the Internet: is there an economic payoff?

U.S. Bureau of Economic Analysis data show that the nation’s rate of yearly output growth between 1995 and 1999 was more than 50% higher than for the period 1987 to 1994. Using state-level data, this study examines foreign capital’s contribution to this upturn in growth. Pooling data for the 50 states in a regression framework showed that foreign capital accounted for 2.6% of overall state output growth for the full period. Foreign capital made no contribution between 1987 and 1994 but accounted for 3.7% of output growth between 1995 and 1999. Furthermore, estimates show that foreign capital had a much larger impact on the manufacturing sector, accounting for more than 16.7% of state manufacturing output growth between 1995 and 1999.

How Information Technology Affects Wages: Evidence Using Internet Usage As a Proxy for IT Skills

As the pervasiveness of the Internet spreads rapidly, Peter Drucker’s prediction about the coming of the new organization, labeled as the “knowledge society” [7] or the “virtual corporation” [9] is now a reality. In an information-based economy, any radical shift in our approach toward information and knowledge influences more than an elite group of individuals or firms—it has a far-reaching effect on national and global economies. The Internet is viewed by many as a paradigm shift forcing individuals, firms, businesses, and even societies to rapidly adapt to a newfound virtual world in which agility and responsiveness are the hallmarks of success [5]. At a 1999 meeting of Congress’s Joint Economic Committee Microsoft Chairman Bill Gates told committee members: “We will absolutely see productivity increases coming out of the use of technology for many years to come.” At same meeting, Federal Reserve Chairman Alan Greenspan told the panel that “something special has happened to the American economy in recent years because of computerization.” That “something special” was the increased productivity generated by the Internet and information technology [10]. Bureau of Labor Statistics data at least superficially support this linkage showing the share of employees using a computer at work rising from 25% in 1984 to 52% in 1997. Computer usage, in this context, refers to the use of computers to perform any work-related function, such as word processing, information retrieval, data analysis, and other related tasks. In addition to enhancing productivity, revolutionary technologies such as the Internet revive hopes of removing barriers to economic prosperity, increasing workplace productivity, and improving quality of life. The much-proclaimed anonymity of the Internet user leads to the hypothesis that the Internet may help close racial and gender-based wage gaps. The significant increase in women using the Web since its early origins [8] suggests a relationship between the Internet, gender, and the wage structure, but little or no research has been done in this area. Could the Internet lead to a full realization of the legal concept of equal pay for equal work?