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Benjamin A. Olken

Bio: Benjamin A. Olken is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Corruption & Poverty. The author has an hindex of 43, co-authored 138 publications receiving 11590 citations. Previous affiliations of Benjamin A. Olken include National Bureau of Economic Research & Harvard University.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors used historical fluctuations in temperature within countries to identify its effects on aggregate economic outcomes, and found that higher temperatures substantially reduce economic growth in poor countries, not just the level of output.
Abstract: This paper uses historical fluctuations in temperature within countries to identify its effects on aggregate economic outcomes. We find three primary results. First, higher temperatures substantially reduce economic growth in poor countries. Second, higher temperatures may reduce growth rates, not just the level of output. Third, higher temperatures have wide-ranging effects, reducing agricultural output, industrial output, and political stability. These findings inform debates over climate’s role in economic development and suggest the possibility of substantial negative impacts of higher temperatures on poor countries. (JEL E23, O13, Q54, Q56)

1,275 citations

Journal ArticleDOI
TL;DR: A rapidly growing body of research applies panel methods to examine how temperature, precipitation, and windstorms influence economic outcomes as mentioned in this paper, including agricultural output, industrial output, labor productivity, energy demand, health, conflict, and economic growth.
Abstract: A rapidly growing body of research applies panel methods to examine how temperature, precipitation, and windstorms influence economic outcomes. These studies focus on changes in weather realizations over time within a given spatial area and demonstrate impacts on agricultural output, industrial output, labor productivity, energy demand, health, conflict, and economic growth, among other outcomes. By harnessing exogenous variation over time within a given spatial unit, these studies help credibly identify (i) the breadth of channels linking weather and the economy, (ii) heterogeneous treatment effects across different types of locations, and (iii) nonlinear effects of weather variables. This paper reviews the new literature with two purposes. First, we summarize recent work, providing a guide to its methodologies, datasets, and findings. Second, we consider applications of the new literature, including insights for the "damage function" within models that seek to assess the potential economic effects of future climate change. ( JEL C51, D72, O13, Q51, Q54)

1,057 citations

ReportDOI
TL;DR: In this paper, the authors present a randomized field experiment on reducing corruption in over 600 Indonesian village road projects, finding that increasing government audits from 4 percent of projects to 100 percent reduced missing expenditures, as measured by discrepancies between official project costs and an independent engineers' estimate of costs.
Abstract: This paper presents a randomized field experiment on reducing corruption in over 600 Indonesian village road projects. I find that increasing government audits from 4 percent of projects to 100 percent reduced missing expenditures, as measured by discrepancies between official project costs and an independent engineers’ estimate of costs, by eight percentage points. By contrast, increasing grassroots participation in monitoring had little average impact, reducing missing expenditures only in situations with limited free-rider problems and limited elite capture. Overall, the results suggest that traditional topdown monitoring can play an important role in reducing corruption, even in a highly corrupt environment.

826 citations

Journal ArticleDOI
TL;DR: This article investigated the mechanisms through which leaders affect growth and found that autocrats affect growth directly, through fiscal and monetary policy, and also influence political institutions that, in turn, appear to affect growth.
Abstract: Economic growth within countries varies sharply across decades. This paper examines one explanation for these sustained shifts in growth - changes in the national leader. We use deaths of leaders while in office as a source of exogenous variation in leadership, and ask whether these randomly-timed leadership transitions are associated with shifts in country growth rates. We find robust evidence that leaders matter, particularly in autocratic settings. Moreover, the death of autocrats appears to lead towards improvements in growth. We investigate the mechanisms through which leaders affect growth and find that autocrats affect growth directly, through fiscal and monetary policy. Autocrats also influence political institutions that, in turn, appear to affect growth. In particular, we find that small movements toward democracy following the death of an autocrat appear to improve growth, while dramatic democratizations are associated with reductions in growth. The results suggest that individual leaders can play crucial roles in shaping the growth of nations.

813 citations

ReportDOI
Abstract: Recent years have seen a remarkable expansion in economists' ability to measure corruption. This in turn has led to a new generation of well-identified, microeconomic studies. We review the evidence on corruption in developing countries in light of these recent advances, focusing on three questions: how much corruption is there, what are the efficiency consequences of corruption, and what determines the level of corruption? We find robust evidence that corruption responds to standard economic incentive theory but also that the effects of anticorruption policies often attenuate as officials find alternate strategies to pursue rents.

656 citations


Cited by
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Book
01 Jan 2009

8,216 citations

Journal ArticleDOI
TL;DR: In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects as discussed by the authors, which has reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas in empirical microeconomics.
Abstract: Many empirical questions in economics and other social sciences depend on causal effects of programs or policies. In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects. This recent theoreti- cal literature has built on, and combined features of, earlier work in both the statistics and econometrics literatures. It has by now reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas of empirical microeconomics. In this review, we discuss some of the recent developments. We focus primarily on practical issues for empirical research- ers, as well as provide a historical overview of the area and give references to more technical research.

3,175 citations

Posted Content
TL;DR: In this paper, the authors investigated conditions sufficient for identification of average treatment effects using instrumental variables and showed that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect.
Abstract: We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced to change their participation status by changing the value of the instrument. Finally we derive the probability limit of the standard IV estimator under these conditions. It is seen to be a weighted average of local average treatment effects.

3,154 citations

Journal ArticleDOI
TL;DR: This article found that most indicators of institutional quality used to establish the proposition that institutions cause growth are constructed to be conceptually unsuitable for that purpose and also found that some of the instrumental variable techniques used in the literature are flawed.
Abstract: We revisit the debate over whether political institutions cause economic growth, or whether, alternatively, growth and human capital accumulation lead to institutional improvement. We find that most indicators of institutional quality used to establish the proposition that institutions cause growth are constructed to be conceptually unsuitable for that purpose. We also find that some of the instrumental variable techniques used in the literature are flawed. Basic OLS results, as well as a variety of additional evidence, suggest that (a) human capital is a more basic source of growth than are the institutions, (b) poor countries get out of poverty through good policies, often pursued by dictators, and (c) subsequently improve their political institutions.

2,543 citations

Journal ArticleDOI
TL;DR: The authors proposed a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit, and GMM that enables cluster-robust inference when there is two-way or multiway clustering that is nonnested.
Abstract: In this article we propose a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit, and GMM. This variance estimator enables cluster-robust inference when there is two-way or multiway clustering that is nonnested. The variance estimator extends the standard cluster-robust variance estimator or sandwich estimator for one-way clustering (e.g., Liang and Zeger 1986; Arellano 1987) and relies on similar relatively weak distributional assumptions. Our method is easily implemented in statistical packages, such as Stata and SAS, that already offer cluster-robust standard errors when there is one-way clustering. The method is demonstrated by a Monte Carlo analysis for a two-way random effects model; a Monte Carlo analysis of a placebo law that extends the state–year effects example of Bertrand, Duflo, and Mullainathan (2004) to two dimensions; and by application to studies in the empirical literature where two-way clustering is present.

2,542 citations