Aggregate Elasticity Research Articles

SUBSTITUTION BETWEEN CLEAN AND DIRTY ENERGY WITH BIASED TECHNICAL CHANGE

AbstractThe elasticity of substitution between clean and dirty energy lies at the center of leading economic analyses of climate policy. Despite the importance, empirical assessments of this key parameter remain scarce. This article estimates the clean‐dirty elasticity of substitution using data on French manufacturing firms. Using the elasticity estimates, I then measure the bias in technical change at the firm level and find that technical change was largely biased toward dirty energy, despite a recent shift toward clean technologies. Finally, I recover the aggregate elasticity that combines substitution within firms and reallocation across firms from the micro elasticity estimates.

Structural policies, FDI and economic stability effects on employment elasticities: case of emerging economies

The focus of this paper is centred on distinguishing between labour and product market policy ( Lmp and Pmp ) indicator’s role to empirically examine if foreign direct investment (FDI) and economic stability (GDPG volatility) effect the employment’s sensitivity to output fluctuations in 44 countries from Africa and Middle East Area over the period of 2000–2017. To address this objective, in the first step we provide by OLS the cross-sectional employment elasticities. Then, unlike previous studies, which are based only on linear specifications, this paper propose different nonlinear specifications to assess the floating marginal effect of the structural indicators. In a third step, each augmented nonlinear model is used to deduce the role of macroeconomic indicators. Based on U- or N-shaped floating marginal effect of only a single structural labour or product market policy ( Lmp or Pmp ), the Lmp indicator is found to have the important increasing impact on employment elasticities which depends on the initial policy condition. Based on augmented cubic model, to maximise employment responsiveness, structural policies have to be complemented by macroeconomic stability policies. Furthermore, the estimations confirm that FDI triggers aggregate employment elasticities and then employment follows the FDI promotions.

Explaining the decline of China's labor share: A wide replication of Oberfield and Raval (2021)

SummaryChina's labor share has declined since late 1990s. Using the methodology developed by Oberfield and Raval, this paper estimates China's aggregate capital‐labor elasticity of substitution, leveraging the estimated micro‐level elasticities. The findings indicate that China's aggregate capital‐labor elasticity falls within the range of 0.9 to 1. Utilizing this estimated aggregate elasticity for labor share decomposition, we find that the bias of technical change emerges as the predominant factor driving the decline in labor share.

Gains from trade: Demand, supply, and idiosyncratic shocks

SummaryFirm‐level sales are often used as a proxy for productivity to quantify welfare gains from trade (GFT) using firm‐level data. This approach ignores the fact that heterogeneity in firm‐level sales is driven by factors other than productivity. Our theoretical and empirical analysis reveals that using sales as a proxy conflates persistent productivity with transitory demand and supply shocks, resulting in an over‐dispersed productivity distribution. Assigning this shock‐inflated productivity to a modeled economy's supply‐side results in overestimated GFT. We show how to obtain unbiased productivity estimates, aggregate trade elasticities, and GFT estimates by exploiting the revenue production function from a single‐source country.

Increasing returns to scale and markups

I estimate aggregate and industry-specific elasticities of scale and markups for the U.S. economy over the period from 1980 to 2019 using data on publicly traded companies. I apply Olley–Pakes and Ackerberg–Caves–Frazer estimation methods and find that the aggregate elasticity of scale for the U.S. economy is 1.1 and has been rising. The elasticity of scale in turn serves as an input for calculating industry markups. Increasing returns to scale help explain observed increases in markups over the last decades for broad sectors of the economy. My estimate of 1.2 for the aggregate markup is significantly lower than the estimate of 1.6 found in recent literature. The large disparity in markup estimates stems from differences in the treatment of fixed and variable costs and the methodological approach to the calculation of markups.

Influence of demand and supply factors on trade flows: Evidence for Argentina (1996–2016)

AbstractUsing an ARDL‐ECM model, we estimate the aggregate and sectoral elasticities for Argentina. We confirm that the income elasticities of exports are lower than those of imports. When we control by real labor costs, exchange rate volatility, the black‐market exchange rate and domestic absorption, the difference between income elasticities is reduced but remains statistically significant. In the sectoral breakdown, the higher the technological intensity in the industry, the higher the income elasticities. Agro‐based, textile, automotive, process, and engineering products have price elasticities two or three times the magnitude of aggregate elasticity.

Macroeconomic Implications of Uniform Pricing

We compile a new database of grocery prices in Argentina. We find uniform pricing both within and across regions—i.e., prices almost do not vary within the stores of a chain. In line with uniform pricing, prices in stores of chains operating in one region react to changes in regional employment while prices in multiregion chains do not. Using a quantitative regional model with multiregion firms and uniform pricing, we find a one-half smaller elasticity of prices to a regional than an aggregate shock. This result highlights that some caution may be necessary when using regional shocks to estimate aggregate elasticities. (JEL D22, L11, L81, O14, O18, R32)

Aggregate elasticity of substitution between skills: estimates from a macroeconomic approach

AbstractWe estimate the elasticity of substitution between high-skill and low-skill workers using panel data from 32 countries during 1970–2015. Most existing estimates, which are based only on US microdata, find a value close to 1.6. We bring international data together with a theory-informed macro-approach to provide new evidence on this important macroeconomic parameter. Using the macro-approach, we find that the elasticity of substitution between tertiary-educated workers and those with lower education levels falls between 1.7 and 2.6, which is higher than previous estimates but within a plausible range. In some specifications, estimated elasticity is above the value required for strong skill-bias of technology, suggesting strong skill-bias is possible.

Minimum-Wage Increases and Low-Wage Employment: Evidence from Seattle

Seattle raised its minimum wage to as much as $11 in 2015 and as much as $13 in 2016. We use Washington State administrative data to conduct two complementary analyses of its impact. Relative to outlying regions of the state identified by the synthetic control method, aggregate employment at wages less than twice the original minimum—measured by total hours worked—declined. A portion of this reduction reflects jobs transitioning to wages above the threshold; the aggregate analysis likely overstates employment effects. Longitudinal analysis of individual Seattle workers matched to counterparts in outlying regions reveals no change in the probability of continued employment but significant reductions in hours, particularly for less experienced workers. Job turnover declined, as did hiring of new workers into low-wage jobs. Analyses suggest aggregate employment elasticities in the range of —0.2 to —2.0, concentrated on the intensive margin in the short run and largest among inexperienced workers. (JEL J22, J23, J24, J31, J38, R23)

Employment elasticity of output growth in Kazakhstan economy: Recent evidence from a macroeconomic perspective

This study aims to understand the dynamics of aggregate and sectorial employment elasticity of output growth in the Kazakhstan economy from 1996 to 2019. To serve our purpose, a rolling regression method with a window of 6 years has been used to estimate aggregate and sectoral employment elasticity, and an ARDL bounds testing approach has been incorporated to assess the impact of various macroeconomics determinants. The results indicate the existence of a cointegration relationship, and the employment elasticity of output growth in Kazakhstan's economy has declined at aggregate and sectoral levels, thus indicating jobless growth. More specifically, the results reveal that inflation, trade openness and the exchange rate are negatively associated with employment elasticity. In contrast, a positive association is established between service sector employment share, the population growth rate and employment elasticity of output growth. The study recommends strengthening macroeconomic fundamentals such as inflation and exchange rate stabilization coupled with robust development of human capital.

What drives innovation? Lessons from COVID-19 R&D

This paper studies the global R&D effort to fight the deadliest diseases. We find: (1) the elasticity of R&D effort with respect to market size is about 1/2 in the cross-section of diseases; (2) given this elasticity, the R&D response to COVID-19 has been 4 to 26 times greater than that implied by its market size; (3) the aggregate short-term elasticity of science and innovation can be very large, as demonstrated by the aggregate flow of clinical trials increasing by 38% in 2020, with limited crowding out of trials for non-COVID diseases; and (4) public institutions and government-led incentives were a key driver of the COVID-19 R&D effort—with public research institutions accounting for 70 percent of all COVID-19 clinical trials globally. Overall, our work suggests that leveraging early-stage incentives, non-monetary incentives, and public institutions may be important for scaling up global innovation.

Micro-mechanisms behind declining labor shares: Rising market power and changing modes of production

I derive a micro-founded framework showing how rising firm market power on product and labor markets and falling aggregate labor output elasticities provide three competing explanations for falling labor shares. I apply my framework to 20 years of German manufacturing sector micro data containing firm-specific price information to study these three distinct drivers of declining labor shares. I document a severe increase in firms’ labor market power, whereas firms’ product market power stayed comparably low. Changes in firm market power and a falling aggregate labor output elasticity each account for one half of the decline in labor's share.

Injury severity analysis of motorcycle crashes: A comparison of latent class clustering and latent segmentation based models with unobserved heterogeneity

The latent class clustering and latent segmentation-based models are employed to account for heterogeneity across different groups. Further, the random parameter variants of these modeling frameworks are employed to consider heterogeneity within the group. Both of these approaches have recently gained significant attention in road safety literature. However, the similarities and differences between these two methods are seldom explained and investigated. To that end, this study proposes to compare the performance of latent class clustering and latent segmentation-based random parameter models in examining crash injury severity outcomes. These models have been developed based on an ordered logit modeling framework to accommodate the ordinal nature of injury severity levels. For examining crash injury severity outcomes, this is the first study to consider the random parameter variant of ordered modeling structure within a latent segmentation modeling scheme. The current study also tests for and incorporates temporal instability of exogenous variables across multiple years of crash data in examining injury severity outcomes. The models have been estimated by using motorcycle crash data of Queensland, Australia, from the year 2012 through 2016. The comparison exercise is also augmented by estimating aggregate level elasticity effects of exogenous variables. The comparison exercise highlights the superiority of the latent segmentation approach in examining injury severity compared to the latent class clustering-based modeling approach. Moreover, the random parameter variants of both frameworks performed better than their fixed-parameter counterparts, which highlights the need to account for both across- and within-group heterogeneity. The temporal stability tests indicate that the effects of exogenous variables on the rider injury severity are different across year-wise models.

Differential influence of human impacts on age‐specific demography underpins trends in an African elephant population

AbstractDiagnosing age‐specific influences on demographic trends and their drivers in at‐risk wildlife species can support the development of targeted conservation interventions. Such information also underpins understanding of life history. Here, we assess age‐specific demography in wild African elephants, a species whose life history is marked by long life and extreme parental investment. During the 20‐yr study, survival and its variation were similar between adults and juveniles in contrast to relationships found among many large‐bodied mammals. Prospective analysis on age‐specific Leslie matrices for females demonstrated survival is more influential than fecundity on λ, with sensitivity of both decreasing with age. Results aggregated by stage classes indicate young adults (9–18 yr) demonstrated the highest elasticity, followed by preparous juveniles (3–8 yr). Mature adults (36+ yr) had the lowest aggregate elasticity value. Retrospective analysis parameterized by data from the early and latter periods of the study, characterized by low then high human impact (faster and slower growth, respectively), demonstrated fecundity (particularly for adults; 19–35 yr) explained the greatest variation in λ observed during the period of low human impact, while survival (particularly juvenile and adult) was more influential during the high human impact period. The oldest females (mature adult stage) weakly influenced population growth despite demonstrating the highest fecundity and their behavioral importance in elephant society. Multiple regression models on survival showed the negative effects of human impacts and population size were the strongest correlates across sexes and ages. Annual rainfall, our metric for environmental conditions, was weakly informative. The presence of dependent young was positively correlated with survival for breeding females, suggesting condition‐based mortality filtering during pregnancy. Notwithstanding the stabilizing effect of high juvenile survival on elephant population growth, demographic processes in elephants were similar to those shaping life history in other large herbivores. Implications of the study results with respect to the conservation of elephants and analysis of demographic impact of poaching are discussed, along with the study's relevance to theories regarding the evolution of life history and parental care.

Fields from Afar: Evidence of Heterogeneity in United States Corn Rotational Response from Remote Sensing Data

We construct estimates of own‐ and cross‐price corn rotation elasticities using a field‐level dataset that accounts for over 83% of the US corn‐producing area. We allow rotational response to vary by estimating separate models across 115 subsamples that we delineate using Major Land Resource Areas (MLRAs) and soil characteristics. The results show a high degree of rotational response heterogeneity. Across the country, we find that rotational response is elastic in some areas and near zero in others. After aggregating the results to the national level, we find that modeling rotational response without allowing for heterogeneity produces a short‐run own‐price elasticity of corn planting of around 0.50, which conforms to the latest estimates in the literature. When allowing heterogeneous price sensitivity, our preferred estimate of the rotation elasticity is 0.69. This is evidence that imposing a uniform rotation response could seriously bias aggregate elasticity estimates.

Micro Data and Macro Technology

We develop a framework to estimate the aggregate capital‐labor elasticity of substitution by aggregating the actions of individual plants. The aggregate elasticity reflects substitution within plants and reallocation across plants; the extent of heterogeneity in capital intensities determines their relative importance. We use micro data on the cross‐section of plants to build up to the aggregate elasticity at a point in time. Interpreting our econometric estimates through the lens of several different models, we find that the aggregate elasticity for the U.S. manufacturing sector is in the range of 0.5–0.7, and has declined slightly since 1970. We use our estimates to measure the bias of technical change and assess the decline in labor's share of income in the U.S. manufacturing sector. Mechanisms that rely on changes in the relative supply of factors, such as an acceleration of capital accumulation, cannot account for the decline.

Escorting and mode choice decisions of members of an urban university in New Delhi, India

This paper explores the escorting and mode choice decisions of members – faculties, staff, and married students – of an urban university in New Delhi, India. The decisions relating to school travel of children of members of a university are captured using a primary travel behavior survey. The data is further segmented based on residence location of university members, i.e., on-campus and off-campus housing. Descriptive analysis is followed by a multinomial logit model, employed to study the escorting person and mode choice decisions. This study finds similarities and differences in behaviors. Respondents staying inside the campus own more cars and motorcycles as compared to the respondents staying outside the campus. However, those staying outside possessed more bicycles than the respondents living inside the university. Further, irrespective of the location of residences, parents holding higher educational qualifications are reluctant to walk/bicycle their children to school. For on-campus residents, household car (and two-wheeler) ownership leads to fathers using personal cars for pick-up and drop off children. Household car ownership also negatively influences mothers' intentions to use active modes for child escorting. Further, for both on-campus and off-campus residents, even if households perceive the environment to be safe and secure, they have a higher dependency on private vehicles, especially by mothers. This study also estimates aggregate elasticity effects of relevant variables and discusses, from a broad viewpoint, the policy implications of the findings.

Can Hong Kong price-manage its public transportation’s ridership?

This paper is motivated by the usefulness of own- and cross-price elasticity estimates in managing Hong Kong’s demand for public transportation. It uses a 12-year sample of monthly data from January 2006 to December 2017 to estimate a Generalized Leontief system of six mode-specific passenger volume regressions. Its key findings are: (1) the own-price elasticity estimates are −0.45 for taxi, −0.30 for minibus, −0.24 for bus, −0.23 for ferry, −0.06 for tram, and −0.07 for train (i.e., Mass Transit Railway); (2) the cross-price elasticity estimates are positive and smaller in size than the own-price elasticity estimates; and (3) the aggregate own-price elasticity estimate is −0.048 for the entire public transportation system. These findings of low price responsiveness imply that reducing public transportation fares and raising private transportation’s average usage cost will likely have a minimal impact on Hong Kong public transportation’s ridership. Hence, mitigating Hong Kong’s traffic congestion and vehicular emissions may require such policy measures as restricting private car ownership and improving Hong Kong public transportation’s non-fare attributes of accessibility and travel time performance.

Environment Versus Jobs: An Industry-Level Analysis of Sweden

The aim of this paper was to investigate whether the environment and employment compete with each other in Swedish manufacturing industry. The effect of a marginal increase in environmental expenditure and environmental investment costs on sector-level demand for labor (employment) was studied using a detailed firm-level panel dataset for the period 2001–2008. The results showed that the sign and magnitude of the net employment effects ultimately depend on the aggregate sector-level output demand elasticity. If the output demand is inelastic, these costs induce small net improvements in employment, while a more elastic output demand suggests negative, but in most sectors relatively small, net effects on demand for labor. Hence, the results did not generally indicate a substantial trade-off between jobs and the environment. The general policy recommendation that can be drawn from this study is that, in the absence of empirically estimated output demand elasticities, a careful attitude regarding national environmental initiatives for sectors exposed to world market competition should be adopted.

WHAT DETERMINES THE ELASTICITY OF SUBSTITUTION BETWEEN CAPITAL AND LABOR? A LITERATURE REVIEW

AbstractThis paper provides the first comprehensive review of the empirical and theoretical literature on the determinants of the elasticity of substitution between capital and labor. Our focus is on the two‐input constant elasticity of substitution (CES) production function. We start by presenting four concise observations that summarize the empirical literature on the estimation of . Motivated by these observations, the main part of this survey then focuses on potential determinants of capital–labor substitution. We first review several approaches to the microfoundation of production functions where the elasticity of substitution (EOS) is treated as a purely technological parameter. Second, we outline the construction of an aggregate elasticity of substitution (AES) in a multi‐sectoral framework and investigate its dependence on underlying intra‐ and inter‐sectoral substitution. Third, we discuss the influence of the institutional framework on the extent of factor substitution. Overall, this survey highlights that the effective elasticity of substitution (EES), which is typically estimated in empirical studies, is generally not an immutable deep parameter but depends on a multitude of technological, non‐technological, and institutional determinants. Based on these insights, the final section identifies a number of potential empirical and theoretical avenues for future research.