Local Job Multipliers in the United States: Variation with Local Characteristics and with High-Tech Shocks

Abstract

This paper provides new estimates of local job multipliers, the ratio of total jobs generated to some initial number of jobs created from a demand shock. Multipliers greatly affect benefits versus costs of local job-creation policies. These new estimates rely on improved methodology and data. The methodology better captures dynamic effects of demand shocks, specifies the model so that demand shocks are more comparable, and is more general in the types of demand shocks that are considered. The data has more industry detail than that used in previous studies. The local job multipliers estimated tend to be about one-quarter lower than typically estimated local multipliers, closer to 1.5 than to 2.0. In addition, demand shocks to all industries matter, not just to tradable industries. Multipliers are similar across different types of geographic areas, with county multipliers being only one-quarter below commuting zone multipliers and state multipliers only one-quarter above commuting zone multipliers. Multipliers are not larger for larger commuting zones, but they increase in commuting zones that have lower initial employment to population ratios. Multipliers are higher for high-tech industries, particularly in commuting zones with a larger initial high-tech share. In such high-tech local economies, hightech multipliers may be close to 3. While our high-tech multipliers are greater than for other industries, our estimated high-tech multipliers are less than in some prior studies.

Heterogeneity in the local employment multipliers in the United States

“…As a result, we use the shift-share instrument to obtain the reduced form of estimates and the 2SLS estimates. These results are consistent with the findings by Bartik and Sotherland (2019). The first-stage F-statistic is greater than 10, suggesting that, weak instrumentation is not a concern.…”

“…The 2SLS estimated coefficient of 1.072 is relatively larger than the reduced form of estimate of 0.829. The averaged reduced form of multiplier ranges between 1.600 and 1.829, which is within the range of typically estimated local employment multipliers (see, e.g., Bartik & Sotherland, 2019;Jones & Yang, 2018;Partridge et al, 2017;Tsvetkova & Partridge, 2016;van Dijk, 2017van Dijk, , 2018. The 2SLS estimates may appear to be an improvement over the OLS estimates but as noted by Bartik and Sotherland (2019), the 2SLS approach omits some of the agglomeration and congestion effects following a demand shock.…”

“…The 2SLS estimates may appear to be an improvement over the OLS estimates but as noted by Bartik and Sotherland (2019), the 2SLS approach omits some of the agglomeration and congestion effects following a demand shock. As discussed previously, the OLS estimates are likely to be inconsistent as the estimates rely on all variation in the employment.…”

“…OSEI and SEnGUPTa (Bartik & Sotherland, 2019;Moretti, 2010). It was therefore not surprising that, in September 2017, when Amazon announced that it would build a second headquarters (HQ2), almost all US metropolitan statistical areas (MSAs) 1 with a population of over 1 million entered the bidding contest.…”

“…Starting from the seminal contribution of Moretti (2010), a growing body of empirical studies has estimated local employment multipliers (Adams, 2016;Bartik & Sotherland, 2019;van Dijk, 2017van Dijk, , 2018Fuller & Chapman, 2018;Gerolimetto & Magrini, 2016;Jones & Yang, 2018;Partridge, Rickman, Rose Olfert, & Tan, 2017;Tsvetkova & Partridge, 2016). Moretti (2010) used the shift-share instrumental variable's strategy to estimate the local multiplier effect in the US between 1980 and 2000.…”