Abstract:  

This paper studies the effects of infrastructure investment on the labor market. Between 1920 and 1950, the US government began constructing its first interstate highways, the Numbered Highway System. Regions gaining access to the Numbered Highway System experienced significant population growth alongside a shift from self-employment to salaried jobs. To identify the causal effect of this highway network on local labor markets, I use a novel instrumental variable approach exploiting a hypothetical set of highways proposed by the US Army for national defense. I further interpret these causal effects through a spatial equilibrium model in which highway construction induces households to select out of self-employment as local agglomeration—manifested in higher land costs and denser markets—increases the fixed cost of production near highways. I find that investment in the Numbered Highway System can account for one fifth of the decline in the aggregate self-employment rate over this period, underscoring how infrastructure investment fosters regional integration and structural change.

Abstract: 

This paper illustrates how chained price indices trade off updating quality standards against maintaining transitivity. Updating quality standards frequently allows price indices to reflect ongoing product innovation, but introduces path dependence, whereby measured inflation depends on the sequence of comparisons used to construct an index. Fixing quality standards ensures transitivity but limits the ability of an index to incorporate new information about quality growth. I develop a locally transitive geometric quality-adjusted unit value index (GQAUV) that provides a structured way to characterize and reconcile this tradeoff. The key insight is that standard bilateral indices implicitly redefine quality standards in each comparison, causing standards to drift over time. When these comparisons are chained, the evolving quality standard generates path dependence in measured inflation. In contrast, the proposed index proceeds in two stages: it first constructs quality-adjusted price changes that are transitive within a pre-specified window of time, and then aggregates these comparisons across overlapping windows, effectively averaging across alternative quality standards used to measure inflation. Using data on the U.S. automobile market, I show that the locally transitive GQAUV yields higher measured inflation as transitivity is enforced over longer time horizons. These results suggest that differences across price indices can be understood as reflecting alternative choices about how and when quality standards are updated, providing a unified perspective on the tradeoff between transitivity and timely quality adjustment.

Abstract: 

Businesses, individuals, and government policymakers rely on accurate and timely measurement of nominal sales, inflation, and real output, but current official statistics face challenges on a number of dimensions. First, these key indicators are derived from surveys conducted by multiple agencies with different time frames, yielding a complex integration process. Second, some of the source data needed for the statistics (e.g., expenditure weights) are only available with a considerable lag.  Third, response rates are declining, especially for high-frequency surveys. Focusing on retail trade statistics, we document important discrepancies between official statistics and measures computed directly from item-level transactions data. The long lags in key components of the source data delay recognition of economic turning points and lead to out-of-date information on the composition of output. We provide external data sources to validate the transactions data when their nominal sales trends differ importantly from official statistics. We then conduct counterfactual exercises that replicate the methodology that official statistical agencies use with the transactions data in the construction of nominal sales indices. These counterfactual exercises produce similar results to the official statistics even when the official nominal sales and item-level transactions data exhibit different trends.

Abstract:  

The growing availability of item-level transaction data has led to widespread use of unit value indices (UVIs), which are computed from the ratio of total sales to units sold.  For a homogeneous good, the UVI estimates the average price change.  For heterogeneous goods, the UVI conflates pure price changes with shifts in product mix, so can mismeasure inflation. This paper derives an exact decomposition of the UVI into average within-good price changes and changes in product-mix due to changes in the composition of continuing, entering, and exiting products; constructs a quality-adjusted unit value index (QUVI) that deflates price levels using quality adjustment factors estimated using hedonic procedures; characterizes conditions under which the QUVI produces bounds on the exact price index; and derives a decomposition of the QUVI that facilitates comparisons of the UVI and QUVI.