Systems estimation of a structural model of distribution and demand in the US economy

Arbeitspapier

Empirical studies of income distribution and aggregate demand using a structural modeling approach typically find that demand is wage-led in most large, advanced economies. These studies have been criticized for estimating the individual equations for consumption, investment, and net exports separately, treating total output and the wage share as exogenous, which could lead to simultaneity bias. This paper corrects for such possible bias as well as common shocks to the equations by using systems GMM estimation applied to annual US data for 1963-2016. This paper is also the first to provide separate estimates of nonresidential and residential investment functions and to distinguish the effects of shocks to different underlying determinants of the wage share (unit labor costs and firms' monopoly power). Surprisingly, the GMM estimates imply that private-sector aggregate demand is more, rather than less, wage-led (or in some cases, less profit-led) compared with OLS estimates of identically specified models.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: FMM Working Paper ; No. 54

Classification and Topics

• Classification: Wirtschaft ; General Aggregative Models: Keynes; Keynesian; Post-Keynesian ; Aggregate Factor Income Distribution ; Economic History: Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations: U.S.; Canada: 1913- ; Economywide Country Studies: U.S.; Canada ; Multiple or Simultaneous Equation Models: Instrumental Variables (IV) Estimation
• Subject: income distribution ; wage-led demand ; profit-led demand ; US economy ; systems estimation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Blecker, Robert A. ; Cauvel, Michael ; Kim, Yun
• Event: Veröffentlichung
• (who): Hans-Böckler-Stiftung, Macroeconomic Policy Institute (IMK), Forum for Macroeconomics and Macroeconomic Policies (FMM)
• (where): Düsseldorf
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/246819
• Last update: 10.03.2025, 11:42 AM CET