We develop a unified framework to trace value added along global supply chains in the presence of foreign direct investment by decomposing either GDP based on forward linkages or final production based on backward linkages. The new framework accounts for the presence of foreign invested...

This paper uses simulations to explore the properties of the HP filter of Hodrick and Prescott (1997), the BK filter of Baxter and King (1999), and the H filter of Hamilton (2018) that are designed to decompose a univariate time series into trend and cyclical components. Each simulated time...

Recent work highlights a falling entry rate of new firms and a rising market share of large firms in the United States. To understand how these changing firm demographics have affected growth, we decompose productivity growth into the firms doing the innovating. We trace how much each firm...

This chapter provides a comprehensive overview of decomposition methods that have been developed since the seminal work of Oaxaca and Blinder in the early 1970s. These methods are used to decompose the difference in a distributional statistic between two groups, or its change over time, into...

How to best utilize the wide range of estimates of elasticities that characterize econometric literature when using calibrated models is the issue we address here through a blending of econometrics and calibration into calibmetrics. Econometrically generated literature based elasticity...

This paper presents ex post decomposition analysis of wage inequality change using multi-sector general equilibrium models. The analytical structure used is a specific- factors model of trade, which we calibrate to UK data for the two years 1979 and 1975. We first calibrate our general...

This paper notes a potential problem in the method of Blinder and Oaxaca the most popular method in the literature for decomposing the mean difference between groups of a given variable into the portion attributable to differences in the distribution of some explanatory variables and differences...

I use a vector autoregressive model (VAR) to decompose an individual firm's stock return into two components: changes in cash-flow expectations (i.e., cash-flow news) and changes in discount rates (i.e., expected-return news). The VAR yields three main results. First, firm-level stock returns...

This paper shows that unexpected stock returns must be associated with changes in expected future dividends or expected future returns A vector autoregressive method is used to break unexpected stock returns into these two components. In U.S. monthly data in 1927-88, one-third of the variance of...

We propose and study properties of several estimators of variance decomposition in the local-projections framework. We find for empirically relevant sample sizes that, after being bias corrected with bootstrap, our estimators perform well in simulations. We also illustrate the workings of our...