Knowledge that Transforms

The paper provides evidence of the effects of changes in transport costs on the geographic concentration of industries. The analysis uses micro-level commodity flow data and micro-geographic plant-level data to construct industry-specific ad valorem trucking rates and continuous measures of geographic concentration. The findings show that, controlling for international trade exposure and input-output links, increasing trucking rates are significantly associated with declining geographic concentration. The effect is large: changes in trucking rates explain around 20 percent of the observed decline in geographic concentration of Canadian manufacturing industries between 1992 and 2008.

Abstract In an economic theory of suicide, we model social cohesion of the religious community and religious beliefs about afterlife as two mechanisms by which Protestantism increases suicide propensity. We build a unique microregional data set of 452 Prussian counties for 1816 to 1821 and 1869 to 1871, when religiousness was still pervasive. Exploiting the concentric dispersion of Protestantism around Wittenberg, our instrumental variable model finds that Protestantism had a substantial positive effect on suicide. Results are corroborated in first-difference models. Tests relating to the two mechanisms based on historical church attendance data and modern suicide data suggest that the sociological channel plays the more important role.

July 01 2018 Review of Economics and Statistics over the Past 100 Years: Authorship Asim I. Khwaja, Asim I. Khwaja Search for other works by this author on: This Site Google Scholar Kunal Mangal Kunal Mangal Search for other works by this author on: This Site Google Scholar Author and Article Information Asim I. Khwaja Kunal Mangal Online Issn: 1530-9142 Print Issn: 0034-6535 © 2018 The President and Fellows of Harvard College and the Massachusetts Institute of Technology2018 The Review of Economics and Statistics (2018) 100 (3): i–v. https://doi.org/10.1162/rest_e_00743 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Asim I. Khwaja, Kunal Mangal; Review of Economics and Statistics over the Past 100 Years: Authorship. The Review of Economics and Statistics 2018; 100 (3): i–v. doi: https://doi.org/10.1162/rest_e_00743 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThe Review of Economics and Statistics Search Advanced Search This content is only available as a PDF. © 2018 The President and Fellows of Harvard College and the Massachusetts Institute of Technology2018 Article PDF first page preview Close Modal You do not currently have access to this content.

October 01 2018 Review of Economics and Statistics over the Past 100 Years: Content Asim I. Khwaja, Asim I. Khwaja Search for other works by this author on: This Site Google Scholar Kunal Mangal Kunal Mangal Search for other works by this author on: This Site Google Scholar Author and Article Information Asim I. Khwaja Kunal Mangal Online Issn: 1530-9142 Print Issn: 0034-6535 © 2018 The President and Fellows of Harvard College and the Massachusetts Institute of Technology2018The President and Fellows of Harvard College and the Massachusetts Institute of Technology The Review of Economics and Statistics (2018) 100 (4): i–vi. https://doi.org/10.1162/rest_e_00766 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Asim I. Khwaja, Kunal Mangal; Review of Economics and Statistics over the Past 100 Years: Content. The Review of Economics and Statistics 2018; 100 (4): i–vi. doi: https://doi.org/10.1162/rest_e_00766 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThe Review of Economics and Statistics Search Advanced Search This content is only available as a PDF. © 2018 The President and Fellows of Harvard College and the Massachusetts Institute of Technology2018The President and Fellows of Harvard College and the Massachusetts Institute of Technology Article PDF first page preview Close Modal You do not currently have access to this content.

This paper uses world running records by age to estimate a biological frontier of decline rates. Two models are compared: a linear/ quadratic (LQ) model and a nonparametric model. Two estimation methods are used: (a) minimizing the squared difference between the observed records and the modeled biological frontier and (b) using extreme value theory to estimate the biological frontier that maximizes the probability of observing the existing world records by age. The results support the LQ model and suggest a linear percentage decline up to the late 70s and quadratic decline after that.

On March 18, 1976, the Swedish parliament voted on a bill that, if approved, would have substantially increased both the scale and scope of government representation on bank boards. Since parliament was hung, the outcome of the vote was decided by a lottery. We exploit this lottery to study the causal effect on shareholder value of government involvement in the corporate governance of banks. We find that the rejection of the bill resulted in positive abnormal returns that persisted in the following days. The results suggest that unsolicited government involvement in the corporate governance of banks is harmful for owners.

This paper analyzes the transfer pricing of multinational firms. Intrafirm prices may systematically deviate from arm’s-length prices for two motives: pricing to market and tax avoidance. Using French firm-level data on arm’s-length and intrafirm export prices, we find that the sensitivity of intrafirm prices to foreign taxes is reinforced once we control for pricing-to-market determinants. Most important, we find no evidence of tax avoidance if we disregard tax haven destinations. Tax avoidance through transfer pricing is economically sizable. The bulk of this loss is driven by the exports of 450 firms to ten tax havens.

This paper builds on the composite likelihood concept of Lindsay (1988) to develop a framework for parameter identification, estimation, inference, and forecasting in dynamic stochastic general equilibrium (DSGE) models allowing for stochastic singularity. The framework consists of four components. First, it provides a necessary and sufficient condition for parameter identification, where the identifying information is provided by the first- and second-order properties of nonsingular submodels. Second, it provides a procedure based on Markov Chain Monte Carlo for parameter estimation. Third, it delivers confidence sets for structural parameters and impulse responses that allow for model misspecification. Fourth, it generates forecasts for all the observed endogenous variables, irrespective of the number of shocks in the model. The framework encompasses the conventional likelihood analysis as a special case when the model is nonsingular. It enables the researcher to start with a basic model and then gradually incorporate more shocks and other features, meanwhile confronting all the models with the data to assess their implications. The methodology is illustrated using both small- and medium-scale DSGE models. These models have numbers of shocks ranging between 1 and 7.

Can a toolbox of simple heuristic rules help explain lottery choices relative to expected utility theory (EUT)? While a mixture model of EUT plus heuristic rules will obviously fit data better than EUT only, given the small sample sizes, there is a danger of overfitting. Therefore, instead of goodness-of-fit measures, we focus on forecasting performance. Using two data sets of binary lottery choices and reasonable holdout subsets for testing forecasting performance, we find that the EUT-only model forecasts better than the toolbox mixture model with EUT. Even when the toolbox model with EUT fits the data significantly better, EUT-only forecasts better.

This paper introduces a simple measure of a concordance pattern among observed outcomes along a network, that is, the pattern in which adjacent outcomes tend to be more strongly correlated than nonadjacent outcomes. The graph concordance measure can be generally used to quantify the empirical relevance of a network in explaining cross-sectional dependence of the outcomes, and as shown in the paper, it can also be used to quantify the extent of homophily under certain conditions. When one observes a single large network, it is nontrivial to make inferences about the concordance pattern. Assuming a dependency graph, this paper develops a permutation-based confidence interval for the graph concordance measure. The confidence interval is valid in finite samples when the outcomes are exchangeable, and under the dependency graph, an assumption together with other regularity conditions, is shown to exhibit asymptotic validity. Monte Carlo simulation results show that the validity of the permutation method is more robust than the asymptotic method to various graph configurations.