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« Back to Results

From Micro Data To Macro Policy

Paper Session

Saturday, Jan. 4, 2020 12:30 PM - 2:15 PM (PDT)

Manchester Grand Hyatt, Harbor C
Hosted By: Korea-America Economic Association
  • Chair: Yoosoon Chang, Indiana University

Identifying Modern Macro Equations with Old Shocks

Regis Barnichon
,
Federal Reserve Bank of San Francisco and CEPR
Geert Mesters
,
Pompeu Fabra University

Abstract

Despite decades of research, the consistent estimation of structural forward-looking macroeconomic equations remains a formidable empirical challenge because of pervasive endogeneity issues. Prominent cases —the estimation of Phillips curves, of Euler equations for consumption or output, or of monetary policy rules— have typically relied on using pre-determined variables as instruments, with mixed success. In this work, we propose a new approach that consists in using sequences of independently identified structural shocks as instrumental variables. Our approach is robust to weak instruments and is valid regardless of the shocks’ variance contribution. We estimate a Phillips curve using monetary shocks as instruments and find that conventional methods (i) substantially under-estimate the slope of the Phillips curve and (ii) over-estimate the role of forward-looking inflation expectations.

A Growth Model of the Data Economy

Laura Veldkamp
,
Columbia University

Abstract

The rise of information technology and big data analytics has given rise to ``the new economy." But are its economics new? This article constructs a classic growth model with data accumulation. Data has three key features: 1) Data is a by-product of economic activity; 2) Data enhances firm productivity; 3) data is information used for forecasting. The model can explain why data-intensive goods or services, like apps, are given away for free, why firm size is diverging, and why many big data firms are unprofitable for a long time. While these transition dynamics differ from those of traditional models, the long run features diminishing returns. Just like capital accumulation, data accumulation alone cannot sustain growth. Without true improvements in productivity, data-driven growth will grind to a halt.

The Making of the Modern Metropolis: Evidence from London

Stephen J. Redding
,
Princeton University
Stephan Heblich
,
University of Bristol
Daniel M. Sturm
,
London School of Economics

Abstract

Modern metropolitan areas involve large concentrations of economic activity and the transport of millions of people each day between their residence and workplace. We use the revolution in transport technology from the invention of steam railways, newly-constructed spatially disaggregated data for London from 1801-1921, and a quantitative urban model to provide evidence on the role of these commuting flows in supporting such concentrations of economic activity. Steam railways dramatically reduced travel times and permitted the first large-scale separation of workplace and residence. We show that our model is able to account for the observed changes in the organization of economic activity, both qualitatively and quantitatively. In counterfactuals, we find that removing the entire railway network reduces the population and the value of land and buildings in Greater London by 20 percent or more, and brings down commuting into the City of London from more than 370,000 to less than 60,000 workers.

Expectations and Firms' Decision-Making: New Evidence

Olivier Coibion
,
University of Texas-Austin

Abstract

We study the relationship between the macroeconomic expectations of firms in France and their economic decisions using a long-running and large scale survey of firms. We find that higher inflation expectations on the part of managers are associated with higher prices and wages, as well as higher employment and investment. Similar results hold when managers expect higher aggregate wage growth and faster aggregate economic activity. We study how these results differ along a variety of characteristics of firms.
Discussant(s)
Hie Joo Ahn
,
Federal Reserve Board
Hyunju Lee
,
Ryerson University
Eunhee Lee
,
University of Maryland
Yoosoon Chang
,
Indiana University
JEL Classifications
  • E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
  • F4 - Macroeconomic Aspects of International Trade and Finance