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Market Competition and Political Influence: An Integrated Approach
Steven Callander, Stanford University
Dana Foarta, Stanford University
Takuo Sugaya, Stanford University
Juan M. Ortner, Boston University

The operation of markets and of politics are in practice deeply intertwined. Political decisions set the rules of the game for market competition and, conversely, market competitors participate in and influence political decisions. Callander, Foarta, and Sugaya develop an integrated model to capture the circularity between the two domains. The researchers show that a positive feedback loop emerges such that market power begets political power in a positive feedback loop, but that this feedback loop is bounded. With too much market power, the balance between politics and markets itself becomes lopsided and this drives a wedge between the interests of a policymaker and the dominant firm. Although such a wedge would seem pro-competitive, Callander, Foarta, and Sugaya show how it can exacerbate the static and dynamic inefficiency of market outcomes. More generally, their model demonstrates that intuitions about market competition can be upended when competition is intermediated by a strategic policymaker.

Ideology and Performance in Public Organizations
Jorg L. Spenkuch, Northwestern University
Edoardo Teso, Northwestern University
Guo Xu, University of California, Berkeley and NBER
John M. de Figueiredo, Duke University and NBER

Spenkuch, Teso, and Xu combine personnel records of the United States federal bureaucracy from 1997-2019 with administrative voter registration data to study how ideological alignment between politicians and bureaucrats affects the personnel policies and performance of public organizations. They first show three stylized facts on the ideological preferences of federal bureaucrats. (i) Consistent with the use of the spoils system to align ideology at the highest levels of government, the researchers find significant partisan cycles and substantial turnover among political appointees. (ii) By contrast, Spenkuch, Teso, and Xu find virtually no political cycles in the civil service. The lower levels of the federal government resemble a "Weberian" bureaucracy that appears to be largely insulated from partisan cycles. (iii) Democrats make up the plurality of civil servants. Overrepresentation of Democrats increases with seniority, with the difference in career progression being explained by positive selection on observables. They then show that political misalignment carries a sizeable performance penalty. Exploiting presidential transitions as a source of "withinbureaucrat" variation in the political alignment of procurement officers over time, the researchers find that contracts overseen by a misaligned officer exhibit higher cost overruns. Spenkuch, Teso, and Xu provide evidence that is consistent with a general "morale effect," whereby misaligned bureaucrats are less motivated to pursue the organizational mission. Their results thus help to shed light on the costs of ideological misalignment within public organizations.


This paper was distributed as Working Paper 28673, where an updated version may be available.

Is Journalistic Truth Dead? Measuring How Informed Voters Are about Political News
Charles Angelucci, Massachusetts Institute of Technology
Andrea Prat, Columbia University

How many voters are informed about political news mainstream journalists consider important? Angelucci and Prat develop a methodology that combines a protocol for identifying major news stories, online surveys, and the estimation of a model that disentangles individual information precision from news story salience and partisanship. Angelucci and Prat focus on news about U.S. politics in a monthly sample of 1,000 voters repeated 8 times. On average, 85% of individuals are able to distinguish the major real news story of the month from fake news. 59% of individuals confidently believe this news story to be true, 39% are uncertain, and 3% confidently believe it to be false. Their results indicate that the starkest pattern about the ability of voters to identify major news stories is not the generalized death of truth or its ideological polarization but rather its unequal distribution along socioeconomic lines.

Social Media and Xenophobia: Theory and Evidence from Russia
Leonardo Bursztyn, University of Chicago and NBER
Georgy Egorov, Northwestern University and NBER
Ruben Enikolopov, New Economic School
Maria Petrova, Universitat Pompeu Fabra

Bursztyn, Egorov, Enikolopov, and Petrova study the causal effect of social media on ethnic hate crimes and xenophobic attitudes in Russia using quasi-exogenous variation in social media penetration across cities. Higher penetration of social media led to more ethnic hate crimes, but only in cities with a high pre-existing level of nationalist sentiment. Consistent with a mechanism of coordination of crimes, the effects are stronger for crimes with multiple perpetrators. Bursztyn, Egorov, Enikolopov, and Petrova implement a national survey experiment and show that social media persuaded young and low-educated individuals to hold more xenophobic attitudes, but did not increase their openness to expressing these views. Their results are consistent with a simple model of social learning where penetration of social networks increases individuals' propensity to meet like-minded people.


This paper was distributed as Working Paper 26567, where an updated version may be available.

Social Media and Newsroom Production Decisions
Julia Cagé, Sciences Po
Nicolas Hervé, Institut National de l'Audiovisuel
Béatrice Mazoyer, CentraleSupélec

Social media affects not only the way Cagé, Hervé, and Mazoyer consume news, but also the way news is produced, including by traditional media outlets. In this paper, Cagé, Hervé, and Mazoyer study the propagation of information from social media to mainstream media, and investigate whether news editors are influenced in their editorial decisions by stories popularity on social media. To do so, the researchers build a novel dataset including a representative sample of all tweets produced in French between July 2018 and July 2019 (1.8 billion tweets, around 70% of all tweets in French during the period) and the content published online by about 200 mainstream media during the same time period, and develop novel algorithms to identify and link events on social and mainstream media. To isolate the causal impact of popularity, Cagé, Hervé, and Mazoyer rely on the structure of the Twitter network and propose a new instrument based on the interaction between measures of user centrality and news pressure at the time of the event. Cagé, Hervé, and Mazoyer show that story popularity has a positive effect on media coverage, and that this effect varies depending on media outlets’ characteristics. These findings shed a new light on their understanding of how editors decide on the coverage for stories, and question the welfare effects of social media.

AI-tocracy: the Symbiosis of Autocrats and Innovators
Martin Beraja, Massachusetts Institute of Technology and NBER
Andrew Kao, Harvard University
David Y. Yang, Harvard University and NBER
Noam Yuchtman, London School of Economics
Nancy Qian, Northwestern University and NBER

Can frontier innovation be promoted and sustained under autocracy? Beraja, Kao, Yang, and Yuchtman argue that a symbiotic relationship between frontier innovation and entrenched autocracy can exist. Symbiosis arises when (i) innovative output increases autocrats’ probability of maintaining power, and (ii) autocrats’ spending on innovative output to maintain power generates further innovation. The researchers evaluate these two conditions of symbiosis in China’s facial recognition AI sector. Beraja, Kao, Yang, and Yuchtman gather comprehensive data on firms and government procurement contracts in this sector, as well as on social unrest across China during the last decade. Beraja, Kao, Yang, and Yuchtman show that, first, autocrats benefit from AI: local unrest leads to greater government procurement of facial recognition AI, and increased AI procurement suppresses subsequent unrest. Second, the AI sector benefits from autocrats’ suppression of unrest: the contracted AI firms innovate more both for the government and commercial markets. Taken together, these results establish the conditions for sustained AI innovation under the Chinese regime: AI innovation entrenches the regime, and the regime’s investment in AI for political control stimulates further frontier innovation.



Belinda Archibong, Columbia University
Ulrich Eberle, Princeton University
Kai Gehring, University of Bern
Andrew Kao, Harvard University
Thomas Lambert, Rotterdam School of Management, Erasmus University
Roee Levy, Massachusetts Institute of Technology
Zhao Li, Princeton University
Guilherme Lichand, University of Zurich
Zhenqi Liu, Johns Hopkins University
Matt Lowe, University of British Columbia
Nicola Mastrorocco, Trinity College Dublin
Anna Nicińska, University of Warsaw
Massimiliano G. Onorato, University of Bologna
Emanuel Ornelas, Sao Paulo School of Economics
Itzchak T. Raz, Hebrew University
Jonah M. Rexer, Princeton University
Condoleezza Rice, Stanford University
Kenneth Shepsle, Harvard University
Ahmed Skali, Deakin University
Takuo Sugaya, Stanford University
Ana-Maria Tenekedjieva, Federal Reserve Board
Gabriel Z. Tourek, Massachusetts Institute of Technology
Ana Tur-Prats, University of California at Merced

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