Abstract not found

We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros (“nonevents”). In many literatures, these variables have proven difficult to explain and predict, a problem that seems to have at least two sources. First, popular statistical procedures, such as logistic regression, can sharply underestimate the probability of rare events. We recommend corrections that outperform existing methods and change the estimates of absolute and relative risks by as much as some estimated effects reported in the literature. Second, commonly used data collection strategies are grossly inefficient for rare events data. The fear of collecting data with too few events has led to data collections with huge numbers of observations but relatively few, and poorly measured, explanatory variables, such as in international conflict data with more than a quarter-million dyads, only a few of which are at war. As it turns out, more efficient sampling designs exist for making valid inferences, such as sampling all available events (e.g., wars) and a tiny fraction of nonevents (peace). This enables scholars to save as much as 99 % of their (nonfixed) data collection costs or to collect much more meaningful explanatory

Abstract not found

ome detail more recent developments in the economic theory of choice, and modifications to this theory that are being forced by experimental evidence from cognitive psychology. I will close with a survey of statistical methods that have developed as part of the research program on economic choice behavior. Science is a cooperative enterprise, and my work on choice behavior reflects not only my own ideas, but the results of exchange and collaboration with many other scholars. 1 First, of course, is my co-laureate James Heckman, who among his many contributions pioneered the important area of dynamic discrete choice analysis. Nine other individuals who played a major role in channeling microeconometrics and choice theory toward their modern forms, and had a particularly important influence on my own work, are Zvi Griliches, L.L. Thurstone, Jacob Marschak, Duncan Luce, Danny Kahneman, Amos Tversky, Moshe Ben-Akiva, Charles Manski, and Kenneth Train. A gallery of their p

This resource paper is intended to give a historical account of the development of the methodology of disaggregate behavioral travel demand analysis and its connection to random utility maximization (RUM). It reviews the early development of the subject, and major methodological innovations over the past three decades in choice theory, data collection, and statistical tools. It concludes by identifying some topics and issues that deserve more work, and fearlessly forecasting the future course of research in the field.

Abstract: This paper studies the econometric problems associated with estimation of a stochastic process that is endogenously sampled. Our interest is to infer the law of motion of a discrete-time stochastic process pt that is observed only at a subset of times t1 tn that depend on the outcome of a probabilistic sampling rule that depends on the history of the process as well as other observed covariates xt. We focus on a particular example where pt denotes the daily wholesale price of a standardized steel product. However there are no formal exchanges or centralized markets where steel is traded and pt can be observed. Instead nearly all steel transaction prices are a result of private bilateral negotiations between buyers and sellers, typically intermediated by middlemen known as steel service centers. Even though there is no central record of daily transactions prices in the steel market, we do observe transaction prices for a particular firm — a steel service center that purchases large quantities of steel in the wholesale market for subsequent resale in the retail market. The endogenous sampling problem arises from the fact that the firm only records pt on the days that it purchases steel. We present a parametric analysis of this problem under the assumption that the timing of steel purchases is part of an optimal trading strategy that maximizes the firm’s expected discounted trading profits. We derive a parametric partial information maximum likelihood (PIML) estimator that solves the endogenous sampling problem and efficiently estimates the unknown parameters of a Markov transition probability that determines the law of motion for the underlying pt process. The PIML estimator also yields estimates of the structural parameters that determine the optimal trading rule. We also introduce an alternative consistent, less efficient, but computationally simpler simulated minimum distance

The paper uses the concept of credit limit to analyze the determinants of household access to and participation in informal and formal credit markets in Malawi. Households are found to be credit constrained, on average, both in the formal and informal sectors; they borrow, on average, less than half of any increase in their credit lines. Furthermore, they are not discouraged in their participation and borrowing decisions by further increases in the formal interest rate and/or the transaction costs associated with getting formal credit. This suggests that getting access to credit is much more important than its cost for these households. Hence, credit policies should focus on making access easier rather than providing credit with subsidized interest rates. The composition of household assets is found to be much more important as a determinant of household access to formal credit than the total value of household assets or landholding size. In particular, a higher share of land and livestock in the total value of household assets is negatively correlated with access to formal credit. However, land remains a significant determinant of access to informal credit. Therefore, poor households whose assets consist mostly of land and livestock but who want to diversify into nonfarm income generation activities may be constrained by lack of capital. As informal loans are usually too small to help poor households start a viable nonfarm iii business, these households may be forced to rely on farming as the sole source of income, despite its unreliability because of the frequency of drought in Malawi. Finally, formal and informal credit are found to be imperfect substitutes. In particular, formal credit, whenever available, reduces but does not completely eliminate informal borrowing...

The objective of IFPRI's multicountry research program on rural financial policies for food security of the poor is to identify policies and institutional arrangements that help the poor integrate themselves into sustainable savings and credit systems such that they have an increased capacity to invest, bear risk, and smooth consumption. The focus of the research on policy and program design and their effects on household investment and consumption requires field data collection at the institutional and household level. This paper presents the underlying conceptual framework and various methodological approaches that have been reviewed and tested by the team at IFPRI and at collaborating institutions. Methodologies are presented for analysis at the institutional level, mainly focusing on the determinants of the formation of financial institutions and the analysis of effects of program design on institutional conduct and performance, and at the household level, thereby addressing determ...

Abstract not found

Correspondence should go to this author.