Nitya Pandalai-Nayar

Department of Economics
University of Texas at Austin
3.142 BRB, 2225 Speedway
Austin, TX 78713
Tel: 503/616-1616

E-Mail: EmailAddress: hidden: you can email any NBER-related person as first underscore last at nber dot org
NBER Program Affiliations: IFM
NBER Affiliation: Faculty Research Fellow
Institutional Affiliation: University of Texas at Austin

NBER Working Papers and Publications

January 2020Technological Transitions with Skill Heterogeneity Across Generations
with Rodrigo Adão, Martin Beraja: w26625
Why are some technological transitions particularly unequal and slow to play out? We develop a theory to study transitions after technological innovations driven by worker reallocation within a generation and changes in the skill distribution across generations. The economy's transitional dynamics have a representation as a q-theory of skill investment. We exploit this in two ways. First, to show that technology-skill specificity and the cost of skill investment determine how unequal and slow transitions are by affecting the two adjustment margins in the theory. Second, to connect these determinants to measurable, short-horizon changes in labor market outcomes within and between generations. We then empirically analyze the adjustment to recent cognitive-biased innovations in developed econ...
June 2019The Global Business Cycle: Measurement and Transmission
with Zhen Huo, Andrei A. Levchenko: w25978
This paper uses sector-level data for 30 countries and up to 28 years to provide a quantitative account of the sources of international GDP comovement. We propose an accounting framework to decompose comovement into the components due to correlated shocks, and to the cross-country transmission of shocks. We apply this decomposition in a multi-country multi-sector DSGE model. We provide an analytical solution to the global influence matrix that characterizes every country's general equilibrium GDP elasticities with respect to shocks anywhere in the world. We then provide novel estimates of country-sector-level technology and non-technology shocks to assess their correlation and quantify their contribution to comovement. TFP shocks are virtually uncorrelated across countries, whereas non-tec...
May 2019Multinationals, Offshoring and the Decline of U.S. Manufacturing
with Christoph E. Boehm, Aaron Flaaen: w25824
We provide new facts about the role of multinationals in the decline in U.S. manufacturing employment between 1993-2011, using a novel microdata panel with firm-level ownership and trade information. Multinational-owned establishments displayed lower employment growth than a narrow control group and accounted for 41% of the aggregate manufacturing employment decline. Further, newly multinational establishments in the U.S. experienced job losses, while their parent firms increased input imports from abroad. We develop a model that rationalizes this behavior and bound a key elasticity with our microdata. The estimates imply that a reduction in the costs of foreign sourcing leads firms to increase imports of intermediates and to reduce U.S. manufacturing employment. Our findings suggest that ...
March 2015TFP, News, and "Sentiments:" The International Transmission of Business Cycles
with Andrei A. Levchenko: w21010
We propose a novel identification scheme for a non-technology business cycle shock, that we label "sentiment." This is a shock orthogonal to identified surprise and news TFP shocks that maximizes the short-run forecast error variance of an expectational variable, alternatively a GDP forecast or a consumer confidence index. We then estimate the international transmission of three identified shocks – surprise TFP, news of future TFP, and "sentiment" – from the US to Canada. The US sentiment shock produces a business cycle in the US, with output, hours, and consumption rising following a positive shock, and accounts for the bulk of short-run business cycle fluctuations in the US. The sentiment shock also has a significant impact on Canadian macro aggregates. In the short run, it is more impor...
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