Saturday, November 6, 2021
Who pays when minimum wage hikes come through the drawn-out demand-supply legislative processes?
This is precisely the question taken up by researchers Christopher Esposito of the University of Chicago and Edward Leamer and Jerry Nickelsburg of UCLA in an interesting working paper series. Drawing on a unique set of mandated wage hikes in the Los Angeles area, they present evidence that minimum wage changes led area restaurants to raise prices, change menu items, obtain lower rents in the high wage areas and, in some cases, caused eateries to shut down.
Results from the paper suggest that policymakers face an important dilemma when designing minimum wage policies to redistribute income while minimizing job loss. So, on one hand, restaurants in high-income neighborhoods studied by the authors passed on the full incidence of the minimum wage differential to their customers suggesting that minimum wages should be set relative to local income levels. The price passthrough channel for income redistribution is optimized when minimum wages are set uniquely for fine-grained spatial units, such as neighborhoods, within which the elasticity of demand for restaurant meals is homogenous. However, on the other hand, their findings also indicate that customers’ demand for restaurant meals can spill across jurisdictional borders with different minimum wages. Therefore, different minimum wages across fine-grained spatial units have the potential to move customer demand, jobs, and tax revenue out of jurisdictions that enact higher minimum wages. A universal minimum wage increase is not sensitive to this heterogeneity in the elasticity of demand, while minimum wage increases enacted at the neighborhood scale may cause restaurants to relocate out of higher-wage areas. The optimal spatial scale for setting minimum wages must balance these two offsetting forces.
In addition to these policy considerations, the study also raises the possibility that some of the incidence of minimum wage increases falls on landlords. The theoretical model predicts that land rents in regions subject to larger minimum wages will decrease, particularly at locations close to areas with lower minimum wages. This proposition is further strengthened because restaurant properties have specific use characteristics which are costly to change.
Click here to read the full explainer article/ full paper.
Source: Esposito et al. (2021). NBER. Who Paid Los Angeles’ Minimum Wage? A Side-by-Side Minimum Wage Experiment in Los Angeles County.
Who pays when minimum wage hikes come through the drawn-out demand-supply legislative processes?
This is precisely the question taken up by researchers Christopher Esposito of the University of Chicago and Edward Leamer and Jerry Nickelsburg of UCLA in an interesting working paper series. Drawing on a unique set of mandated wage hikes in the Los Angeles area, they present evidence that minimum wage changes led area restaurants to raise prices, change menu items,
Posted by 11:00 AM
atLabels: Inclusive Growth
Friday, November 5, 2021
A new paper by Le HaThua & RobertoLeon-Gonzalezb
“Forecasting macroeconomic variables in rapidly changing emerging economies presents a number of challenges. In addition to structural changes, the time-series data are usually available only for a short number of periods, and predictors are available in different lengths and frequencies. Dynamic model averaging (DMA), by allowing the forecasting model to change dynamically over time, permits the use of predictors with different lengths and frequencies for the purpose of forecasting in a rapidly changing economy. This study uses DMA to forecast inflation and growth in Vietnam, Thailand, Philippines, Sri Lanka and Ghana. We compare its forecasting performance with a wide range of other time-series methods. We find that the size and composition of the optimal predictor set changed, indicating changes in the economic relationships over time. We also find that DMA frequently produces more accurate forecasts than other forecasting methods for both inflation and economic growth in the countries studied.”
A new paper by Le HaThua & RobertoLeon-Gonzalezb
“Forecasting macroeconomic variables in rapidly changing emerging economies presents a number of challenges. In addition to structural changes, the time-series data are usually available only for a short number of periods, and predictors are available in different lengths and frequencies. Dynamic model averaging (DMA), by allowing the forecasting model to change dynamically over time, permits the use of predictors with different lengths and frequencies for the purpose of forecasting in a rapidly changing economy.
Posted by 7:08 PM
atLabels: Forecasting Forum
New Paper by Ritong Quc, Allan Timmermanna & Yinchu Zhub
“This paper develops new methods for pairwise comparisons of predictive accuracy with cross-sectional data. Using a common factor setup, we establish conditions on cross-sectional dependencies in forecast errors which allow us to test the null of equal predictive accuracy on a single cross-section of forecasts. We consider both unconditional tests of equal predictive accuracy as well as tests that condition on the realization of common factors and show how to decompose forecast errors into exposures to common factors and idiosyncratic components. An empirical application compares the predictive accuracy of financial analysts’ short-term earnings forecasts across six brokerage firms.”
New Paper by Ritong Quc, Allan Timmermanna & Yinchu Zhub
“This paper develops new methods for pairwise comparisons of predictive accuracy with cross-sectional data. Using a common factor setup, we establish conditions on cross-sectional dependencies in forecast errors which allow us to test the null of equal predictive accuracy on a single cross-section of forecasts. We consider both unconditional tests of equal predictive accuracy as well as tests that condition on the realization of common factors and show how to decompose forecast errors into exposures to common factors and idiosyncratic components.
Posted by 7:04 PM
atLabels: Forecasting Forum
This study, by Michiels, Nordman, and Seetahul, combines behaviorist and structuralist views to understand the extent to which individual skills and personality traits facilitate labor market mobility of disadvantaged groups in the presence of constraining social structures.
Based on a rural India case study, results from this paper show that personality traits are important determinants of labor market mobility but also emphasize a strong rigidity of the socioeconomic structure of the Indian labor market in terms of gender and caste, and its relative stillness over time. While for women, literacy, emotional stability, and openness to new experiences appear to allow income gains, these benefits are limited by the labor market structure, maintaining them in low-skilled and casual occupations. For Dalits, emotional stability and agreeableness seem to play an important role in relative income mobility. These interesting findings highlight the segmented nature of the Indian labor market, which is still strongly organized by diverse forms of domination.
Source: Michiels et al. (2021). Many Rivers to Cross: Social Identity, Cognition, and Labour Mobility in Rural India. Institute of Labor Economics.
Click here to read the full paper.
This study, by Michiels, Nordman, and Seetahul, combines behaviorist and structuralist views to understand the extent to which individual skills and personality traits facilitate labor market mobility of disadvantaged groups in the presence of constraining social structures.
Based on a rural India case study, results from this paper show that personality traits are important determinants of labor market mobility but also emphasize a strong rigidity of the socioeconomic structure of the Indian labor market in terms of gender and caste,
Posted by 9:28 AM
atLabels: Inclusive Growth
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Posted by 5:00 AM
atLabels: Global Housing Watch
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