2021 Panel at SIOE Conference

ALUMNI PRESENT PANEL AT CONFERENCE OF
SOCIETY FOR INSTITUTIONAL AND ORGANIZATIONAL ECONOMICS
June 26, 2021
Virtual conference hosted by the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

Workshop alumni Fernando Arteaga, Boubacar Diallo, Farhan Majid, Juan Felipe Riano, and Jan Vogler presented papers at a session on measuring institutions at the 2021 SIOE conference. Mary Shirley was the organizer and chair, and David Skarbek was the commentator.

Fernando Arteaga
Fernando Arteaga
Boubacar Diallo
Boubacar Diallo
Farhan Majid
Farhan Majid
Juan F. Riano
Juan F. Riano
Jan Vogler
Jan Vogler
David Skarbek
David Skarbek


ABSTRACTS BY THE PANEL

Shipwrecked by Rents
Fernando Arteaga
University of Pennsylvania
Desiree Desierto, George Mason University
Mark Koyama, George Mason University

The trade route between Manila and Mexico was a monopoly of the Spanish Crown for more than 250 years. The ships that sailed this route---the Manila Galleons were "the richest ships in all the oceans", but much of the wealth sank at sea and remain undiscovered. We introduce a newly constructed dataset of all of the ships that traveled this route. We show formally how monopoly rents that allowed widespread bribery would have led to overloading and late ship departure, thereby increasing the probability of shipwreck. Empirically, we demonstrate not only that these late and overloaded ships were more likely to experience shipwrecks or to return to port, but that such effect is stronger for galleons carrying more valuable, higher-rent, cargo. This sheds new light on the costs of rent-seeking in European colonial empires.


Machine Learning Approaches to Testing Institutional Hypotheses: The Case of Acemoglu, Johnson, and Robinson (2001)
Boubacar Diallo

In their seminal 2001 work, Acemoglu, Johnson, and Robinson (AJR) argued that institutions influence economic development, using the logarithm of settler mortality as an instrument to establish a causal effect. A number of economists and other social scientists have challenged this work in terms of both data and identification strategy. One of these criticisms concerned the IV estimated coefficients and standard errors, which were nearly twice as large as the OLS coefficients and standard errors. My research uses machine learning to test the robustness of AJR’s findings. Using the AJR dataset, which I randomly divide into training data and testing data, I am able to predict the average protection against expropriation risk from settler mortality. These predicted values of property rights protection are then regressed on per capita GDP growth. My results indicate a strong and positive effect of property rights protection on growth, consistent with AJR’s earlier results. Moreover, the use of machine learning to obtain institutional values yields estimates close to the OLS estimates, unlike AJR. Removing African countries and neo-European countries such as Canada, Australia, USA, and New Zealand does not alter the sign and significance of the coefficient of interest. These results suggest that machine learning can be helpful to economists facing data issues.


Do “Beef Bans” Affect Women’s Health?
Farhan Majid
IMPAQ International

Wafa Hakim, University of Alabama
Aparajita Dasgupta, Ashoka University

This paper examines the impact of cultural institutions in India on women’s health and development. It investigates a particular cultural institution - the religious norm that bans cattle slaughter and beef sale/possession in much of India. The majority of the Indian population belongs to religions that consider cows to be sacred. In several sacred Hindu texts, the avoidance of beef consumption is established and regularly reinforced as one of the most important practices. The earliest known reference to a legal ban on cow slaughter is an engraving dated 412 CE on a stupa in Sanchi, Madhya Pradesh, during the reign of Chandragupta II of the Gupta dynasty. Studying the effects of such historical religious norms is important but challenging. For this purpose, we compile the first-ever historical state-level panel data on legislation banning cattle slaughter and beef sale/possession in India from 1950 to the present. We collect and assemble legislative data from 26 Indian states in many different local languages, along with federal documents. We devise a variety of identification strategies to get a sense of the causal effect of beef bans. For instance, we look at state level rollout of beef bans over time and compare the effects on upper caste Hindus, Sikhs, and Jains ( who traditionally don’t consume beef) with the effects on lower caste Hindus, Muslims, and Christians (who traditionally do consume beef). We then combine our data on cultural institutions with 1) household and individual level data on beef consumption from national sample surveys and 2) biomarkers from demographic and health surveys. Using a triple difference-in-differences model, we show that beef bans reduce beef consumption, and reduce women’s hemoglobin in communities that traditionally eat beef.


Bureaucratic Nepotism
Juan Felipe Riano Rodriguez
University of British Columbia

This paper studies the anatomy of nepotism within public sector organizations. By linking confidential information on bureaucrat's family ties and administrative employer-employee records on the universe of civil servants in Colombia (2011-2017), I document the pervasiveness of close family ties within the public administration and how this prevalence is negatively related to the performance of bureaucrats and governmental agencies. Then, I show how family connections to top non-elected managers and advisors distort the hiring, promotion, and compensation of civil servants. Consistent with the extraction of private rents instead of better screening of workers, I find that bureaucrats with lower levels of education, higher opportunity costs in the private sector, and more records of misperformance benefit the most from these connections. Finally, I evaluate the 2015 anti-nepotism legislation in Colombia and its impact on the nepotistic returns to family ties. I provide evidence on the limited effectiveness of the reform and show how bureaucrats strategically responded to this policy change by substituting different margins of favouritism and reshuffling within the public administration. Taken together, these findings provide the first systematic empirical examination of public sector nepotism and anti-nepotism legislation in a modern bureaucracy.


Pandemics and Political Development: The Electoral Legacy of the Black Death in Germany
Daniel W. Gingerich, University of Virginia
Jan P. Vogler
University of Virginia

Do pandemics have lasting consequences for political behavior? The authors address this question by examining the consequences of the deadliest pandemic of the last millennium: the Black Death (1347–1351). They claim that pandemics can influence politics in the long run if the loss of life is high enough to increase the price of labor relative to other factors of production. When this occurs, labor-repressive regimes, such as serfdom, become untenable, which ultimately leads to the development of proto-democratic institutions and associated political cultures that shape modalities of political engagement for generations. The authors test their theory by tracing the consequences of the Black Death in German-speaking Central Europe. They find that areas hit hardest by that pandemic were more likely to adopt inclusive political institutions and equitable land ownership patterns, to exhibit electoral behavior indicating independence from landed elite influence during the transition to mass politics, and to have significantly lower vote shares for Hitler’s National Socialist Party in the Weimar Republic’s fateful 1930 and July 1932 elections. (Now published here.)