Payroll Share, Real Wage and Labor Productivity across US States

This paper analyzes regional contributions to the US payroll share from 1977 to 2017 and the four major business cycles throughout this period. We implement two empirical exercises. First, we decompose the US payroll share across states. Utilizing a Divisia index decomposition technique yields exact contributions of real wages, employment structure, labor productivity and relative prices across the states to the aggregate change in the payroll share. Key findings are that the decline in the aggregate (i) is driven by decoupling between real wage and labor productivity; and (ii) is initially driven by the rust belt states, but subsequently dominated by relatively large states. Second, we employ mixture models on real wages and labor productivity across US states to discern whether distinct mechanisms appear to generate these distributions. Univariate models (iii) indicate the possibility that two distinct mechanisms generate state labor productivities, raising the question of whether regional dualism has taken hold. Lastly, we use bivariate mixture models to investigate whether such dualism and decoupling manifest in the joint distributions of payroll shares and labor productivity, too. Results (iv) are affirmative, and further suggest a tendency for high performing states to have relatively high payroll shares initially, and low payroll shares more recently.

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The Decline of the U.S. Labor Share Across Sectors

10.36687/inetwp105 ◽

2019 ◽

pp. 1-37 ◽

Cited By ~ 1

Author(s):

Ivan Mendieta-Muñoz ◽

Codrina Rada ◽

Rudi von Arnim

Keyword(s):

Labor Productivity ◽

Real Wage ◽

Structural Changes ◽

Manufacturing Sector ◽

Dominant Role ◽

Early Period ◽

Relative Prices ◽

Labor Share ◽

Us Economy ◽

The Us

This paper provides novel insights on the changing functional distribution of income in the post– war US economy. We present a Divisia index decomposition of the US labor share (1948–2017) by fourteen sectors. The decomposition method furnishes exact contributions from four components towards aggregate changes of the labor share: sectoral real compensation, sectoral labor productivity, the structure of the economy as measured by employment shares, and the structure of markets as measured by relative prices. Results are presented for the entire period as well as the “golden age” (1948–1979) and a “neoliberal era” (1979–2017), painting a rich and detailed picture of structural changes in the US economy. The manufacturing sector plays a dominant role: despite its continuously falling employment share, growth of real compensation matches that of labor productivity in the early period but falls far behind during the neoliberal era. Further, employment shifts towards stagnant sectors with relatively low real wages and productivity. We discuss these results in the context of Baumol’s and Lewis’s seminal contributions on dual economies. While the cost disease is apparent—employment shifts towards stagnant sectors, their relative prices rise, and the aggregate growth rate (of productivity) decreases—the originally suggested mechanism of upward real wage convergence is muted. The observed changes are instead compatible with a “reverse-Lewis” shift, where stagnant sectors act as a labor surplus sink, and dynamic sector labor experiences slowing real wage growth.

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Convergence of labor productivity across the US states

Economic Modelling ◽

10.1016/j.econmod.2018.08.008 ◽

2019 ◽

Vol 76 ◽

pp. 270-280 ◽

Cited By ~ 5

Author(s):

Bisrat Kinfemichael ◽

A.K.M. Mahbub Morshed

Keyword(s):

Labor Productivity ◽

Us States ◽

The Us

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Panel Estimation for the Relationship between Real Wage, Inflation and Labor Productivity for OECD Countries

International Conference on Eurasian Economies 2019 ◽

10.36880/c11.02305 ◽

2019 ◽

Author(s):

Sevilay Konya ◽

Zeynep Karaçor ◽

Mücahide Küçüksucu

Keyword(s):

Labor Productivity ◽

Real Wage ◽

Slovak Republic ◽

Oecd Countries ◽

Panel Estimation ◽

Economic Literature ◽

Real Wages ◽

Wage Inflation ◽

The Relationship ◽

Cointegration Relationship

There are studies examining the relationship between real wage, inflation and labor productivity in the economic literature. Increase in real wages causes to an increase in labor productivity. On the other hand, productivity increases also induce inflation to fall. Therefore, the aim of this study is to investigate the relationship between real wage, inflation and labor productivity in the 22 OECD countries (Australia, Belgium, Canada, Chile, Czech Republic, France, Greece, Hungary, Japan, Korea, Latvia, Luxembourg, Mexico, Netherlands, New Zealand, Poland, Portugal, Slovak Republic, Slovenia, Spain, Turkey, United States) in the period of 1995-2017 by panel data methods. According to results, the cointegration relationship between real wage, inflation and labor productivity was found. In addition, mutual causality was determined between the variables we discussed.

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Real Wages and Labor Productivity in Britain and Germany, 1871–1938: A Unified Approach to the International Comparison of Living Standards

The Journal of Economic History ◽

10.1017/s0022050710000331 ◽

2010 ◽

Vol 70 (2) ◽

pp. 400-427 ◽

Cited By ~ 13

Author(s):

Stephen Broadberry ◽

Carsten Burhop

Keyword(s):

Labor Productivity ◽

Real Wage ◽

Service Sector ◽

Wage Gap ◽

Living Standards ◽

Industrial Workers ◽

Unified Approach ◽

Real Wages ◽

Sectoral Differences ◽

German Worker

Throughout the period 1871–1938, the average British worker was better off than the average German worker, but there were significant differences between major sectors. For the aggregate economy, the real wage gap was about the same as the labor productivity gap, but again there were important sectoral differences. Compared to their productivity, German industrial workers were poorly paid, whereas German agricultural and service sector employees were overpaid. This affected the competitiveness of the two countries in these sectors. There were also important differences in comparative real wages by skill level, affecting the extent of poverty.

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A novel approach to the classification of performance on inpatient perception of hospitalization experience across the US 52 states

10.21203/rs.2.14225/v1 ◽

2019 ◽

Author(s):

Tung-Hui Jen ◽

Tsair-Wei Chien ◽

Willy Chou

Keyword(s):

Healthcare Providers ◽

Us States ◽

High Performing ◽

Novel Approach ◽

The Us ◽

Choropleth Maps ◽

Applied Approach ◽

Consumer Assessment ◽

Domain Scores

Abstract Background: Medical groups identified as high-performing with different approaches have been proposed for classification of performance in the literature, but no consistently-applied approach exists for identifying high performers for the benefit of healthcare providers. Most organizations classify hospitals using domain scores and assign a letter grade (e.g., from A to F in Leapfrog Groups) to the performance level. Whether bibliometrics can be an alternative for classifying healthcare givers’ performances is worthy of study. This study was performed to visualize survey results about inpatients’ perceptions of hospitalization experience for the US states using bibliometrics. Methods: We downloaded the 2014 summaries of HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Services) data. Four indices of h, PI, Ag, and x were applied to evaluate performance based on the core domains derived from the ten domain scores for each state in the US, and then displayed online dashboards to show hospitalization satisfaction across states on Google Maps. Choropleth maps were plotted for classifying the performnces into six grades using the quantiles method.Results: The top three states for hihg quality-of-care are Louisiana, Nebraska, and South Dakota using either x or Ag-index to assess. The Ag-index earns the mean correlation coefficient (=0.86) higher than the other three. The inpatient perception of hospitalization experience or the US states were classified and displayed on choropleth maps. Conclusions: The classification of healthcare performance is sensitive to the domain scores, the approach in classification, and the choice of metrics. The absence of a consistently-applied approach to identify healthcare performers impedes efforts to reliably compare, select, and reward high-performing providers. The x-index is recommended for quantifying the performance of healthcare givers in the foreseeable future.

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Exchange Rate Adjustments and US Trade with China: What does a State Level Analysis Tell Us?

Global Economy Journal ◽

10.1515/gej-2016-0059 ◽

2017 ◽

Vol 17 (2) ◽

pp. 20160059

Author(s):

Firat Demir ◽

Chen Wu

Keyword(s):

Exchange Rate ◽

Real Exchange Rates ◽

State Level ◽

Trade Flows ◽

Relative Prices ◽

Us States ◽

Long Run ◽

The Us ◽

Exchange Rate Changes ◽

Level Analysis

In this paper we explore the trade effects of bilateral real exchange rate changes between the 50 US states and China over the period of 2005–2012. The empirical results based on state-level trade flows and state-level relative prices suggest that the long-run real exchange rates elasticity of US exports to China is in the range of [–3.77, –2.85] and that of Chinese exports to the US is in the range of [–0.23, –3.34]. We also find that state-level differences in human capital and financial development are significant determinants of their export performances with respect to China. Based on the most optimistic scenario, our results suggest that the RMB needs to further appreciate against the dollar by at least 1.8 percent a year for 16 years for the US to achieve balanced trade with China.

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Improved Automated Detection of Subpixel-Scale Inundation—Revised Dynamic Surface Water Extent (DSWE) Partial Surface Water Tests

Remote Sensing ◽

10.3390/rs11040374 ◽

2019 ◽

Vol 11 (4) ◽

pp. 374 ◽

Cited By ~ 22

Author(s):

John Jones

Keyword(s):

Surface Water ◽

Mixture Models ◽

Model Development ◽

Depth Estimation ◽

High Temporal Resolution ◽

Commission Error ◽

Dynamic Surface ◽

In Situ Data ◽

The Us ◽

Spectral Mixture

In order to produce useful hydrologic and aquatic habitat data from the Landsat system, the U.S. Geological Survey has developed the “Dynamic Surface Water Extent” (DSWE) Landsat Science Product. DSWE will provide long-term, high-temporal resolution data on variations in inundation extent. The model used to generate DSWE is composed of five decision-rule based tests that do not require scene-based training. To allow its general application, required inputs are limited to the Landsat at-surface reflectance product and a digital elevation model. Unlike other Landsat-based water products, DSWE includes pixels that are only partially covered by water to increase inundation dynamics information content. Previously published DSWE model development included one wetland-focused test developed through visual inspection of field-collected Everglades spectra. A comparison of that test’s output against Everglades Depth Estimation Network (EDEN) in situ data confirmed the expectation that omission errors were a prime source of inaccuracy in vegetated environments. Further evaluation exposed a tendency toward commission error in coniferous forests. Improvements to the subpixel level “partial surface water” (PSW) component of DSWE was the focus of this research. Spectral mixture models were created from a variety of laboratory and image-derived endmembers. Based on the mixture modeling, a more “aggressive” PSW rule improved accuracy in herbaceous wetlands and reduced errors of commission elsewhere, while a second “conservative” test provides an alternative when commission errors must be minimized. Replication of the EDEN-based experiments using the revised PSW tests yielded a statistically significant increase in mean overall agreement (4%, p = 0.01, n = 50) and a statistically significant decrease (11%, p = 0.009, n = 50) in mean errors of omission. Because the developed spectral mixture models included image-derived vegetation endmembers and laboratory spectra for soil groups found across the US, simulations suggest where the revised DSWE PSW tests perform as they do in the Everglades and where they may prove problematic. Visual comparison of DSWE outputs with an unusual variety of coincidently collected images for locations spread throughout the US support conclusions drawn from Everglades quantitative analyses and highlight DSWE PSW component strengths and weaknesses.

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