I study the effect of demographic change on economic growth under endogenous, R&D-driven technological change. Qualitatively, population ageing generates two opposing forces: increased R&D and capital investments on the one hand, and a decreasing share of workers in the population on the other. I evaluate these channels quantitatively along the demographic transition using a calibrated overlapping generations model with idiosyncratic income risk, mortality risk, intensive and extensive labour supply margins and endogenous technological change. Considering the United States between 1950 and 2100, I find that the demographic transition: (i) increased per-capita output by 0.35 percent per year between 1950 and 2000; (ii) accounts for a 0.65 percentage point decline in growth rates between 1995 and 2025 when the positive growth impact reverts back to trend; and (iii) has no net impact on twenty-first century growth. The main positive driver is endogenous technological change, whose growth contribution more than doubles that of capital deepening between 1950 and 2100. Removing this mechanism eliminates all positive growth effects.
And works in progress
We derive a microfounded, nonhomothetic generalization of all known superlative price indices, including the Fisher, the Törnqvist, and the Sato-Vartia indices. The index varies continuously along the consumption distribution, aggregates consistently across heterogeneous households and largely avoids the need for estimation. In an empirical application to the United States using CEX-CPI data for the period 1995–2020, we find: (i) poor and rich households experience on average the same inflation rate; but (ii) inflation for the poorest decile is more than 2.5 times as volatile as that of the richest decile; and (iii) this higher volatility primarily stems from a larger exposure to price changes in food, gasoline and utilities. Our findings contrast with papers that construct standard price indices for different consumer groups. We show that the inflation inequality uncovered in these analyses may be a spurious result of failing to purge the underlying price indices from a bias owing to income effects on consumer behavior.
We propose a method for constructing nonhomothetic cost-of-living indices when detailed consumption microdata is unavailable. Aggregate prices and expenditure shares together with a single cross-sectional distribution of consumption are sufficient to create a nonhomothetic distribution of cost-of-living indices with our approach. The index is derived from nonhomothetic CES preferences, nests conventional price indices as special cases, and only requires the estimation of one parameter: the elasticity of substitution between necessities and luxuries. The underlying preferences aggregate consistently, which allows us to identify this parameter from aggregate data. We implement the approach using US Personal Consumption Expenditure (PCE) data and construct a nonhomothetic PCE price index covering 72 product groups. This index exhibits annual inflation rates of the poorest ten percent that exceed those of the richest ten percent by 0.8 to 1.1 percentage points throughout most of 2022 to date, thus suggesting that poorer households are hit substantially harder by the current inflation surge.