Bank Efficiency in Transitional Countries: Sensitivity to Stochastic Frontier Design

This article provides an empirical insight on the heterogeneity in the estimates of banking efficiency produced by the stochastic frontier ap- proach. Using data from five countries of Central and Eastern Europe, we study the sensitivity of the efficiency score and the efficiency ranking to a change in the design of the frontier. We found that the average scores are significantly smaller when the transcendental logarithmic functional form is used in the profit efficiency measurement and when the scaling effect is neglected in the cost efficiency measurement. The implied bank ranking is robust to changes in the stochastic frontier definition for cost efficiency, but not for profit efficiency.Banking, Eciency Analysis, Stochastic Frontier Approach, Transitional Countries

Which Foreigners are Worth Wooing? A Meta-Analysis of Vertical Spillovers from FDI

The principal argument for subsidizing foreign investment, especially in developing and transition economies, is the assumed spillover of technology to local firms. Yet researchers report mixed results on spillovers. To examine the phenomenon in a systematic way, we collected 3,626 estimates from 57 empirical studies on between-sector spillovers and reviewed the literature quantitatively. Our results indicate that model misspecifications reduce the reported estimates, but that journals select relatively large estimates for publication. The underlying spillover to suppliers is positive and economically significant, whereas the spillover to buyers is insignificant. Greater spillovers are generated by investors that come from distant countries and that have only slight technological advantages over local firms. In addition, greater spillovers are received by countries that have underdeveloped financial systems and that are open to international trade.Foreign direct investment; Productivity; Spillovers; Meta-analysis; Publication selection bias

Which Foreigners Are Worth Wooing? A Meta-Analysis of Vertical Spillovers from FDI

The principal argument for subsidizing foreign investment is the assumed spillover of technology to local firms. Yet researchers report mixed results on spillovers. To examine the phenomenon in a systematic way, we collected 3,626 estimates from 57 empirical studies on between-sector spillovers and reviewed the literature quantitatively. Our results indicate that model misspecifications reduce the reported estimates, but that journals select relatively large estimates for publication. The underlying spillover to suppliers is positive and economically significant, whereas the spillover to buyers is insignificant. Greater spillovers are received by countries that have underdeveloped financial systems and that are open to international trade. Greater spillovers are generated by investors that come from distant countries and that have only slight technological advantages over local firms.Foreign direct investment, meta-analysis, productivity, publication selection bias, spillovers.

Determinants of Horizontal Spillovers from FDI: Evidence from a Large Meta-Analysis

The voluminous empirical research on horizontal productivity spillovers from foreign investors to domestic firms has yielded mixed results. In this paper, we collect 1,205 estimates of horizontal spillovers from the literature and examine which factors influence spillover magnitude. To identify the most important determinants of spillovers among 43 collected variables, we employ Bayesian model averaging. Our results suggest that horizontal spillovers are on average zero, but that their sign and magnitude depend systematically on the characteristics of the domestic economy and foreign investors. The most important determinants are the technology gap between domestic and foreign firms and the ownership structure in investment projects. Foreign investors who form joint ventures with domestic firms and who come from countries with a modest technology edge create the largest benefits for the domestic economy.Bayesian model averaging, determinants, foreign direct investment, meta-analysis, productivity spillovers.

Bank Efficiency in Transitional Countries: Sensitivity to Stochastic Frontier Design

This article provides an empirical insight on the heterogeneity in the estimates of banking efficiency produced by the stochastic frontier approach. Using data from five countries of Central and Eastern Europe, we study the sensitivity of the efficiency score and the efficiency ranking to a change in the design of the frontier. We found that the average scores are significantly smaller when the transcendental logarithmic functional form is used in the profit efficiency measurement and when the scaling effect is neglected in the cost efficiency measurement. The implied bank ranking is robust to changes in the stochastic frontier definition for cost efficiency, but not for profit efficiency.http://deepblue.lib.umich.edu/bitstream/2027.42/133011/1/wp998.pd

Publication Bias in Measuring Anthropogenic Climate Change

We present a meta-regression analysis of the relation between the concentration of carbon dioxide in the atmosphere and changes in global temperature. The relation is captured by “climate sensitivity”, which measures the response to a doubling of carbon dioxide concentrations compared to pre-industrial levels. Estimates of climate sensitivity play a crucial role in evaluating the impacts of climate change and constitute one of the most important inputs into the computation of the social cost of carbon, which reflects the socially optimal value of a carbon tax. Climate sensitivity has been estimated by many researchers, but their results vary significantly. We collect 48 estimates from 16 studies and analyze the literature quantitatively. We find evidence for publication selection bias: researchers tend to report preferentially large estimates of climate sensitivity. Corrected for publication bias, the bulk of the literature is consistent with climate sensitivity lying between 1.4 and 2.3°C

Does Daylight Saving Save Energy? A Meta-Analysis

The original rationale for adopting daylight saving time (DST) was energy savings. Modern research studies, however, question the magnitude and even direction of the effect of DST on energy consumption. Representing the first meta-analysis in this literature, we collect 162 estimates from 44 studies and find that the mean reported estimate indicates modest energy savings: 0.34% during the days when DST applies. The literature is not affected by publication bias, but the results vary systematically depending on the exact data and methodology applied. Using Bayesian model averaging we identify the most important factors driving the heterogeneity of the reported effects: data frequency, estimation technique (simulation vs. regression), and, importantly, the latitude of the country considered. Energy savings are larger for countries farther away from the equator, while subtropical regions consume more energy because of DST

Death to the Cobb-Douglas Production Function? A Quantitative Survey of the Capital-Labor Substitution Elasticity

We show that the large elasticity of substitution between capital and labor estimated in the literature on average, 0.9, can be explained by three factors: publication bias, use of aggregated data, and omission of the first-order condition for capital. The mean elasticity conditional on the absence of publication bias, disaggregated data, and inclusion of information from the first-order condition for capital is 0.3. To obtain this result, we collect 3,186 estimates of the elasticity reported in 121 studies, codify 71 variables that reflect the context in which researchers produce their estimates, and address model uncertainty by Bayesian and frequentist model averaging. We employ nonlinear techniques to correct for publication bias, which is responsible for at least half of the overall reduction in the mean elasticity from 0.9 to 0.3. Our findings also suggest that a failure to normalize the production function leads to a substantial upward bias in the estimated elasticity. The weight of evidence accumulated in the empirical literature emphatically rejects the Cobb-Douglas specification

Publication Bias in Measuring the Income Elasticity of Water Demand

We present the first meta-analysis of the income elasticity of water demand that accounts for the effects of publication selection (the preferential reporting of estimates that are intuitive and statistically significant). Paradoxically, more affected by publication selection are the otherwise preferable estimates that control for endogeneity. Because such estimates tend to be smaller and less precise, they are often statistically insignificant, which leads to more intense specification searching and bias. Correcting simultaneously for publication and endogeneity biases, we find that the underlying elasticity is approximately 0.15 or less. The result is robust to controlling for 30 other characteristics of the estimates and using Bayesian model averaging to account for model uncertainty. The differences in the reported estimates are systematically driven by differences in the tariff structure, regional coverage, data granularity, and control for temperature in the demand equation

Tuition Reduces Enrollment Less Than Commonly Thought

One of the most frequently examined relationships in education economics is the impact of tuition increases on the demand for higher education. We provide a quantitative synthesis of 443 estimates of this effect reported in 43 studies. While large negative estimates dominate the literature, we show that researchers report positive and insignificant estimates less often than they should. After correcting for this publication bias, we find that the literature is consistent with the mean tuition-enrollment elasticity being close to zero. Nevertheless, we identify substantial heterogeneity among the reported effects: for example, male students and students at private schools react strongly to changes in tuition. The results are robust to controlling for model uncertainty using both Bayesian and frequentist methods of model averaging