Economic implications of better information in a dynamic framework

Summary. We consider an OLG model with accumulation in human capital and analyze the economic implications of information about individual skills. Agents in each period differ by the random innate ability assigned to each individual. When young, all agents are screened for their abilities and this screening process (signal) constitutes a public information which is used in choosing the level of private investment in education. We demonstrate that in the presence of risk sharing markets better information may be harmful for all in equilibrium, and find conditions under which better information either enhances growth or reduces growth.Received: 8 September 2003, Revised: 3 March 2004, JEL Classification Numbers: D80, J24.Correspondence to: Bernhard EckwertWe are pleased to acknowledge the useful comments and suggestions of R. Benabou, Z. Eckstein, E. Helpman, B. Ravikumar and D. Tsiddon. Also, special thanks are given to two anonymous referees. This research was supported by a Grant from G.I.F., the German-Israeli Foundation for Scientific Research and Development.     

Institutions and economic development: How strong is the relation?

This paper investigates the relationship between institutions and economic development (output per worker). As in Hall and Jones (1999), we find that a 1% improvement in institutions (as we measure them) generates on average a 5% increase in output per worker. However, this relationship is not linear and the data have important heterogeneity. Countries with the same value of institutions have different levels of income per worker. We ask whether the “returns to institutions” are the same across countries conditional on the level of institutions. Using quantile regression methods, we show that for countries at the top of the conditional distribution of international incomes, the “returns to institutions” are lower (around 3.8%,) than for countries at the bottom of this distribution (around 6.2%). We show that this result is robust for different model specifications and definitions of institutions. We also provide evidence that, conditional on the level of institutional development, the distribution of output per worker tends to become less disperse as countries improve their institutional framework. In other words, having better institutions is essential in order to close the output-per-worker gap across countries. Finally, we provide the rationale behind the results through a modified version of a Neoclassical Growth Model with time varying wedges, representing policy distortions and institutions.We thank Lee Alston, Roger Koenker, and Stephen L. Parente for helpful discussion, Werner Baer for useful comments, and Chad Jones for facilitating access to the data set. We are also indebted to an anonymous referee and an associate editor for important suggestions that improved the final paper. The analysis, opinions and findings expressed herein represent the views of the authors, they are not necessarily those of the Banco de Portugal. Any remaining errors are our responsibility.First version received: May 2001/Final version received: August 2003     

Community income distributions in a metropolitan area

We extend de Bartolome and Ross [C.A.M. de Bartolome, S.L. Ross, Equilibrium with local governments and commuting: Income sorting vs. income mixing, Journal of Urban Economics 54 (2003) 1–20] to the case when the income distribution in the metropolitan area is a continuous distribution. In particular, we consider a circular central city surrounded by a suburban community. All households must commute to the metropolitan center and public service levels differ in the two jurisdictions. There is intra-jurisdictional and inter-jurisdictional capitalization. Our model has an equilibrium in which the income distributions of the central city and of the suburban community do overlap. Our finding contrasts with the traditional finding of Alonso–Mills–Muth-type models of spatial sorting and of Tiebout-type models of fiscal sorting, both of which have been shown to predict that the income distributions of the two communities do not overlap. In addition, the model explains the fixedness in jurisdictional boundaries.     

Testing the Markov property with high frequency data

This paper develops a framework to nonparametrically test whether discrete-valued irregularly spaced financial transactions data follow a Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates the irregular spacing that characterizes transactions data. Under such an observation rule, the current price duration is independent of a previous price duration given the previous price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Monte Carlo simulations suggest that the asymptotic test has huge size distortions, though a bootstrap-based variant entails reasonable size and power properties in finite samples. As for an empirical illustration, we investigate whether bid–ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid–ask spread. We robustly reject the Markov assumption for two out of the five stocks under scrutiny. Finally, it is reassuring that our results are consistent with two alternative measures of asymmetric information.     

A robust version of the KPSS test based on indicators

This paper proposes a test of the null hypothesis of stationarity that is robust to the presence of fat-tailed errors. The test statistic is a modified version of the so-called KPSS statistic. The modified statistic uses the “sign” of the data minus the sample median, whereas KPSS used deviations from means. This “indicator” KPSS statistic has the same limit distribution as the standard KPSS statistic under the null, without relying on assumptions about moments, but a different limit distribution under unit root alternatives. The indicator test has lower power than standard KPSS when tails are thin, but higher power when tails are fat.     

Corruption, Growth, and Income Distribution: Are there Regional Differences?

This paper uses panel data from 61 countries at different stages of economic development over a 20-year period to investigate regional differences in the effect of corruption on economic growth and income distribution. Using two measures of corruption, we find that there are statistically significant regional differences in the growth and distributional impacts of corruption. The largest growth impact of corruption is found in African countries while OECD and Asian countries have the lowest growth impact. On the other hand, the largest distributional impact of corruption in found in Latin America. A 10% decrease in corruption increases the growth rate of income by about 1.7% in OECD and Asian countries, 2.6% in Latin American countries, and by 2.8% in African countries. A one standard deviation decrease in corruption decreases the gini coefficient of income distribution (0–1 scale) by 0.05 points, 0.14 points, 0.25 points, and 0.33 points in OECD, Asian, African, and Latin American countries, respectively. The results are robust to various specifications, measurement of corruption, measures of investment, as well as the conditioning variables. The results have interesting policy implications for economic growth, especially in low income countries with high rates of corruption.     

Estimating the magnitude of capital flight due to abnormal pricing in international trade: The Russia–USA case

Governmental and international lending agencies, as well as private sector firms, who engage in international trade, have long been concerned with detecting and determining the magnitude of abnormal pricing in international trade. To detect such abnormal pricings, we present a framework analyzing millions of import/export transactions between the U.S. and Russia. The objectives of this study are to estimate the economic impact of over-invoiced/under-invoiced Russian imports/exports from/to the U.S. and to determine if capital movement/capital flight through trade is due to money laundering, tax evasion or some sort of portfolio consideration. Our results lead us to conclude that capital movement through trade in this case can be attributed to either money laundering and/or tax evasion.