Nathan Canen
Biographic Data
| ID | 1471551 |
|---|---|
| NAME | Nathan Canen |
| GIVEN NAMES | Nathan |
| FAMILY NAME | Canen |
| SIGNATURE | CANEN N |
| AFFILIATIONS | University of Houston |
| ORCID | 0000-0002-6444-145X |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 7 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Mitigating policy uncertainty
Elections can lead to substantial policy changes and, thus, are a significant source of risk. Firms can respond to such policy uncertainty by lobbying, but it is hard to quantify whether they do so and, if so, how much lobbying benefits them. We construct a new dataset and leverage investors’ expectations of variability in stock returns in the aftermath of the 2020 US presidential election to generate a new firm‐level measure of exposure to polic…
Quantifying theory in politics
The best empirical research in political science clearly defines substantive parameters of interest, presents a set of assumptions that guarantees their identification, and uses an appropriate estimator. We argue for the importance of explicitly integrating rigorous theory into this process and focus on the advantages of doing so. By integrating a theoretical structure into one’s empirical strategy, researchers can quantify the effects of competi…
How Campaign Ads Stimulate Political Interest
We empirically investigate key dynamic features of advertising competition in elections using a new data set of very high-frequency, household-level television viewing matched to campaign advertising exposures. First, we show that exposure to campaign advertising increases households' consumption of news programming by 3 or 4 minutes on average over the next 24 hours. The identification compares households viewing a program when a political ad ap…
Inference in Linear Dyadic Data Models with Network Spillovers
When using dyadic data (i.e., data indexed by pairs of units), researchers typically assume a linear model, estimate it using Ordinary Least Squares, and conduct inference using “dyadic-robust” variance estimators. The latter assumes that dyads are uncorrelated if they do not share a common unit (e.g., if the same individual is not present in both pairs of data). We show that this assumption does not hold in many empirical applications because in…
Political uncertainty and the forms of state capture
Political Distortions, State Capture, and Economic Development in Africa
This article studies the role of political distortions in driving economic growth and development in Africa. We first discuss how existing theories based on long-run structural factors (e.g., pre-colonial and colonial institutions, or ethnic diversity) may not capture new data patterns in the region, including changes to political regimes, growth patterns, and their variation across regions with similar historical experiences. We then argue that …
Counterfactual analysis under partial identification using locally robust refinement
Structural models that admit multiple reduced forms, such as game‐theoretic models with multiple equilibria, pose challenges in practice, especially when parameters are set identified and the identified set is large. In such cases, researchers often choose to focus on a particular subset of equilibria for counterfactual analysis, but this choice can be hard to justify. This paper shows that some parameter values can be more “desirable” than other…
Political Distortions, State Capture, and Economic Development in Africa
This article studies the role of political distortions in driving economic growth and development in Africa. We first discuss how existing theories based on long-run structural factors (e.g., pre-colonial and colonial institutions, or ethnic diversity) may not capture new data patterns in the region, including changes to political regimes, growth patterns, and their variation across regions with similar historical experiences. We then argue that …
Political uncertainty and the forms of state capture
Counterfactual analysis under partial identification using locally robust refinement
Structural models that admit multiple reduced forms, such as game‐theoretic models with multiple equilibria, pose challenges in practice, especially when parameters are set identified and the identified set is large. In such cases, researchers often choose to focus on a particular subset of equilibria for counterfactual analysis, but this choice can be hard to justify. This paper shows that some parameter values can be more “desirable” than other…
Political uncertainty and the forms of state capture
Political Distortions, State Capture, and Economic Development in Africa
This article studies the role of political distortions in driving economic growth and development in Africa. We first discuss how existing theories based on long-run structural factors (e.g., pre-colonial and colonial institutions, or ethnic diversity) may not capture new data patterns in the region, including changes to political regimes, growth patterns, and their variation across regions with similar historical experiences. We then argue that …
How Campaign Ads Stimulate Political Interest
We empirically investigate key dynamic features of advertising competition in elections using a new data set of very high-frequency, household-level television viewing matched to campaign advertising exposures. First, we show that exposure to campaign advertising increases households' consumption of news programming by 3 or 4 minutes on average over the next 24 hours. The identification compares households viewing a program when a political ad ap…
Inference in Linear Dyadic Data Models with Network Spillovers
When using dyadic data (i.e., data indexed by pairs of units), researchers typically assume a linear model, estimate it using Ordinary Least Squares, and conduct inference using “dyadic-robust” variance estimators. The latter assumes that dyads are uncorrelated if they do not share a common unit (e.g., if the same individual is not present in both pairs of data). We show that this assumption does not hold in many empirical applications because in…
Quantifying theory in politics
The best empirical research in political science clearly defines substantive parameters of interest, presents a set of assumptions that guarantees their identification, and uses an appropriate estimator. We argue for the importance of explicitly integrating rigorous theory into this process and focus on the advantages of doing so. By integrating a theoretical structure into one’s empirical strategy, researchers can quantify the effects of competi…
Mitigating policy uncertainty
Elections can lead to substantial policy changes and, thus, are a significant source of risk. Firms can respond to such policy uncertainty by lobbying, but it is hard to quantify whether they do so and, if so, how much lobbying benefits them. We construct a new dataset and leverage investors’ expectations of variability in stock returns in the aftermath of the 2020 US presidential election to generate a new firm‐level measure of exposure to polic…
Computer Science (5 works) · Economics (5 works) · Political science (4 works) · Politics (4 works) · Electoral Systems and Political Participation (3 works) · Law (3 works) · Econometrics (2 works) · Law (2 works) · Market economy (2 works) · Mathematics (2 works)