We develop a framework that uses price and quantity information on both firms' outputs and inputs to assess the roles, on firm dynamics and welfare, of efficiency, input prices, demand/quality, idiosyncratic markups, and residual wedges. Our strategy nests previous approaches limited by data...

Do recessions speed up or impede productivity-enhancing reallocation? To investigate this question, we use U.S. linked employer-employee data to examine how worker flows contribute to productivity growth over the business cycle. We find that in expansions high-productivity firms grow faster...

We examine whether underlying industry innovation dynamics are an important driver of the large dispersion in productivity across firms within narrowly defined sectors. Our hypothesis is that periods of rapid innovation are accompanied by high rates of entry, significant experimentation and, in...

An important gap in most empirical studies of establishment-level productivity is the limited information about workers' characteristics and their tasks. Skill-adjusted labor input measures have been shown to be important for aggregate productivity measurement. Moreover, the theoretical...

This paper describes the adoption of automation technologies by US firms across all economic sectors by leveraging a new module introduced in the 2019 Annual Business Survey, conducted by the US Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES)....

This paper studies the dynamics of labor demand at the plant and aggregate levels. The correlation of hours and employment growth is negative at the plant level and positive in aggregate time series. Further, hours and employment growth are about equally volatile at the plant level while hours...

This paper presents a new approach to the measurement of the effects of spatial mismatch that takes advantage of matched employer-employee administrative data integrated with a person-specific job accessibility measure, as well as demographic and neighborhood characteristics. The basic...

<i>In response to a comment on this paper by <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3050984">Ayash and Rastad</a href> the authors have posted a comment which may be found <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3113272">here.</a href></i>

This paper uses machine learning (ML) to estimate hedonic price indices at scale from item-level transaction and product characteristics. The procedure uses state-of-the-art approaches from hedonic econometrics and implements them with a neural network ML approach. Applying the methodology to...