This article presents a comprehensive database featuring the digitized, cleaned, geocoded, and linked data of the Swedish manufacturing censuses between 1863 and 1900. The data covers close to the universe of Swedish manufacturing activity and includes establishment-level information on workers, the sum of production value, and toll as output value. The article describes how the data was originally collected and the steps taken to go from raw data to the digital database. We discuss each variable’s definition, how it changed over time, and provide an assessment of the reliability of the data pertaining to each variable. We also assess the quality of the data by comparing it to various other data sources from the same time period. The level of detail in the data makes the users able to both detect and address potential weaknesses of the data. The database offers a unique resource for scholars to study the manufacturing sector during a time of significant transformation in the Swedish industry. To the best of our knowledge, this is among the earliest sources of annual, establishment-level data worldwide. We discuss potential applications for researchers and potential extensions of the database.

Aimed at pandemic preparedness, we construct a framework for integrated epi-econ assessment that we believe would be useful for policymakers, especially at the early stages of a pandemic outbreak. We offer theory, calibration to micro-, macro-, and epi-data, and numerical methods for quantitative policy evaluation. The model has an explicit microeconomic, market-based structure. It highlights trade-offs, within period and over time, associated with activities that involve both valuable social interaction and harmful disease transmission. We compare market solutions with socially optimal allocations. Our calibration to Covid-19 implies that households shift their leisure and work activities away from social interactions. This is especially true for older individuals, who are more vulnerable to disease. The optimal allocation may or may not involve lockdown and changes the time allocations significantly across age groups. In this trade-off, people's social leisure time becomes an important factor, aside from deaths and GDP. We finally compare optimal responses to different viruses (SARS, seasonal flu) and argue that, going forward, economic analysis ought to be an integral element behind epidemiological policy.

Growth has fallen in the U.S. amid a rise in firm concentration. Market share has shifted to low labour share firms, while within-firm labour shares have actually risen. We propose a theory linking these trends in which the driving force is falling overhead costs of spanning multiple products or a rising efficiency advantage of large firms. In response, the most efficient firms (with higher markups) spread into new product lines, thereby increasing concentration and generating a temporary burst of growth. Eventually, due to greater competition from efficient firms, within-firm markups and incentives to innovate fall. Thus our simple model can generate qualitative patterns in line with the observed trends. 

We study structural change in the historical consumption expenditure of the United States, the United Kingdom, Canada, and Australia over more than a century. We characterize the most general class of preferences in a time-additive setting that admits aggregation of the saving decision and allows us to identify preference parameters from aggregate data. We parameterize and estimate such intertemporally aggregable (IA) preferences and discuss their properties in a dynamic general equilibrium framework with sustained growth. Our preference class is considerably more flexible than the Gorman form or PIGL, giving rise to a good fit of the non-monotonic pattern of structural change.

This paper develops a model that generates rising average leisure time and increasing leisure inequality along a path of balanced growth. Households derive utility from three sources: market goods, home goods and leisure. Home production and leisure are both activities that require time and capital. Households allocate time and capital to these non-market activities and supply labor. The dynamics are driven by activity-specific TFP growth and a spread in the distribution of household-specific labor market efficiencies. When the spread is set to replicate the increase in wage inequality across education groups, the model can account for the observed average time series and cross-sectional dynamics of leisure time in the U.S. over the last five decades.

The absence of a trend in hours worked in the postwar United States is an exception: across countries and historically, hours fall steadily by a little below 0.5% per year. Are steadily falling hours consistent with a stable utility function over consumption and leisure under balanced growth of the macroeconomic aggregates? Yes. We fully characterize the class of such functions and thus generalize the well-known “balanced-growth preferences” that demand constant (as opposed to falling) long-run hours. Key to falling hours is an income effect (of steady productivity growth on hours) that slightly outweighs the substitution effect.

For exiting products, statistical agencies often impute inflation from surviving products. This understates growth if creatively-destroyed products improve more than surviving ones. If so, then the market share of surviving products should systematically shrink. Using entering and exiting establishments to proxy for creative destruction, we estimate missing growth in US Census data on non farm businesses from 1983 to 2013. We find missing growth (i) equaled about one-half a percentage point per year; (ii) arose mostly from hotels and restaurants rather than manufacturing; and (iii) did not accelerate much after 2005, and therefore does not explain the sharp slowdown in growth since then.

We propose a new method for computing equilibria in heterogeneous-agent models with aggregate uncertainty. The idea relies on an assumption that linearization offers a good approximation; we share this assumption with existing linearization methods. However, unlike those methods, the approach here does not rely on direct derivation of first-order Taylor terms. It also does not use recursive methods, whereby aggregates and prices would be expressed as linear functions of the state, usually a very high-dimensional object (such as the wealth distribution). Rather, we rely merely on solving nonlinearly for a deterministic transition path: we study the equilibrium response to a single, small “MIT shock” carefully. We then regard this impulse response path as a numerical derivative in sequence space and hence provide our linearized solution directly using this path. The method can easily be extended to the case of many shocks and computation time rises linearly in the number of shocks. We also propose a set of checks on whether linearization is a good approximation. We assert that our method is the simplest and most transparent linearization technique among currently known methods. The key numerical tool required to implement it is value-function iteration, using a very limited set of state variables.

In this paper we use the same methodology as Aghion et al. (2017a) to compute missing growth estimates from creative destruction in France. We find that from 2004 to 2015, about 0.5 percentage point of real output growth per year is missed by the statistical office, which is about the same as what was found in the United States. We look at how missing growth varies across French sectors and regions, and we look at the underlying establishment and firm dynamics. In particular we show that the similar missing growth estimates between France and the United States hide noticeable differences in plant dynamics between the two countries.