Working Papers

Long-Term Macroeconomic Effects of Climate Change: A Cross-Country Analysis, with Matthew E. Kahn, Ryan N. C. Ng, M. Hashem Pesaran, Mehdi Raissi, and Jui-Chung Yang (July 2019).

Abstract: We study the long-term impact of climate change on economic activity across countries, using a stochastic growth model where labour productivity is affected by country-specific climate variables — defined as deviations of temperature and precipitation from their historical norms. Using a panel data set of 174 countries over the years 1960 to 2014, we find that per-capita real output growth is adversely affected by persistent changes in the temperature above or below its historical norm, but we do not obtain any statistically significant effects for changes in precipitation. Our counterfactual analysis suggests that a persistent increase in average global temperature by 0.04°C per year, in the absence of mitigation policies, reduces world real GDP per capita by 7.22 percent by 2100. On the other hand, abiding by the Paris Agreement, thereby limiting the temperature increase to 0.01°C per annum, reduces the loss substantially to 1.07 percent. These effects vary significantly across countries. We also provide supplementary evidence using data on a sample of 48 U.S. states between 1963 and 2016, and show that climate change has a long-lasting adverse impact on real output in various states and economic sectors, and on labour productivity and employment.
JEL Classifications: C33, O40, O44, O51, Q51, Q54.
Key Words: Climate change, economic growth, adaptation, counterfactual analysis.
NBER Working Paper Version: No. 26167
Media Coverage:
This paper has been covered extensively in major international news outlets including the Washington Post, Bloomberg, Fox News, Reuters, CNBC, New York Post, and the Financial Times. It has also been featured in national news agencies in China, India, Japan, the United Kingdom, and the United States, to name a few.
TV interview: Click here to see a Cheddar TV interview with Kamiar Mohaddes. The paper was also covered (including an interview with Kamiar Mohaddes) by CGTN America's Global Business show and CGTN's the World Today show.
Radio Interview: Click here to listen to a radio interview with Kamiar Mohaddes on Olivier Knox’s the Big Picture show on SiriusXM’s POTUS channel.
University of Cambridge News: The paper was also highlighted by the University of Cambridge Research News and the Gates Cambridge Trust.


Illegal Drugs and Public Corruption: Crack Based Evidence from California, with Alessandro Flamini and Babak Jahanshahi (August 2018). 

Abstract: Do illegal drugs foster public corruption? To estimate the causal effect of drugs on public corruption in California, we adopt the synthetic control method and exploit the fact that crack cocaine markets emerged asynchronously across the United States. We focus on California because crack arrived here in 1981, before reaching any other state. Our results show that public corruption more than tripled in California in the first three years following the arrival of crack cocaine. We argue that this resulted from the particular characteristics of illegal drugs: a large trade-off between profits and law enforcement, due to a cheap technology and rigid demand. Such a trade-off fosters a convergence of interests between criminals and corrupted public officials resulting in a positive causal impact of illegal drugs on corruption.
JEL Classifications: C12, D73, K42.
Key Words: Public corruption, crack cocaine, synthetic control method, illegal drugs, and law enforcement. 
CAMA Working Paper Version: No. 39/2018.
Poster: Click here for the poster used at the AEA hosted Poster Session at the 2019 ASSA Annual Meeting.
Interview with the AEA: Alessandro Flamini sat down with the AEA to discuss our paper on how the crack cocaine market fostered public corruption in California during early 1980s. You can watch the interview here.


Debt, Inflation and Growth: Robust Estimation of Long-Run Effects in Dynamic Panel Data Models, with Alexander Chudik, M. Hashem Pesaran, and Mehdi Raissi (November 2013).

Abstract: This paper investigates the long-run effects of public debt and inflation on economic growth. Our contribution is both theoretical and empirical. On the theoretical side, we develop a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in dynamic heterogeneous panel data models with cross-sectionally dependent errors. The relative merits of the CS-DL approach and other existing approaches in the literature are discussed and illustrated with small sample evidence obtained by means of Monte Carlo simulations. On the empirical side, using data on a sample of 40 countries over the 1965-2010 period, we find significant negative long-run effects of public debt and inflation on growth. Our results indicate that, if the debt to GDP ratio is raised and this increase turns out to be permanent, then it will have negative effects on economic growth in the long run. But if the increase is temporary, then there are no long-run growth effects so long as debt to GDP is brought back to its normal level. We do not find a universally applicable threshold effect in the relationship between public debt and growth. We only find statistically significant threshold effects in the case of countries with rising debt to GDP ratios. 
Arabic Abstract: Click here for the Abstract in Arabic. 
JEL Classifications: C23, E62, F34, H6.
Key Words: Long-run relationships, estimation and inference, large dynamic heterogeneous panels, cross-section dependence, debt, inflation and growth, debt overhang. 
CAFE Research Paper: No. 13.23.
Matlab Codes for the CS-DL Estimators: Click here for the Matlab codes for the cross-sectionally augmented distributed lag (CS-DL) Mean Group and Pooled estimators developed in Chudik et al. (2013).
Data and Stata Do File: Click here for the data as well as the Stata do files needed to transform the data and compute the statistics and results in "Debt, Inflation and Growth: Robust Estimation of Long-Run Effects in Dynamic Panel Data Models".
YouTube Video: Click here for a video recording of a lecture given by M. Hashem Pesaran based on "Debt, Inflation and Growth: Robust Estimation of Long-Run Effects in Dynamic Panel Data Models".


Institutions and the Volatility Curse, with Weishu Leong (July 2011).

Abstract: This paper revisits the resource curse paradox and studies the impact of resource rents and their volatility on economic growth under varying institutional quality. Using five-year non-overlapping observations between 1970 and 2005 for 112 countries, we find that while resource rents enhance real output per capita, their volatility exerts a negative impact on economic growth. Therefore, we argue that volatility, rather than abundance per se, drives the resource curse. However, we also find that higher institutional quality can help offset some of the negative volatility effects of resource rents. Therefore, resource abundance can be a blessing provided that growth and welfare enhancing policies and institutions are adopted.
JEL Classifications: C23, F43, O13, O40.
Key Words: Economic growth, resource curse, institutions, resource rent, and commodity price volatility. 
Cambridge Working Paper Version: CWPE 1145.