Estimating Real Income in the United States from 1888 to 1994: Correcting CPI Bias Using Engel Curves

Costa, Dora L.

doi:10.1086/323279

Cited by 137 publications

(209 citation statements)

References 10 publications

(22 reference statements)

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“…7 The OECD adult equivalence scale gives the value 1 to the first person in the household, 0.7 to each additional adult and 0.5 to each additional child (less than 16 years of age).The number given in column one. The estimated income elasticity of food is slightly smaller than in related studies (Costa, 2001;Hamilton, 2001). The US country dummy coefficient is by construction equal to zero, and the dummy coefficients for Azerbaijan, China, Nicaragua, Côte D'Ivoire, Hungary, France, the United Kingdom, and Italy are used to measure the PPP bias relative to the US bias.…”

Section: Main Model Based On Household Surveyscontrasting

confidence: 59%

“…The PPP bias stems from two problems well known in the price index literature: namely, bias caused by differences in quality, and substitution bias (Costa, 2001;Hamilton, 2001;Hill, 2000;Neary, 2004). Most PPP calculations, among them the Geary-Khamis calculations presented in the PWT, belong to the group of fixedbasket calculations.…”

Section: Explaining the Biasmentioning

confidence: 99%

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International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food

Almås

2007

SSRN Journal

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Price-adjusted data on national incomes applied in cross-country comparisons are measured with bias. By studying micro data, this paper finds that the bias is systematic: the poorer a country is, the more its income tends to be overestimated.The price-adjusted data of the Penn World Table are applied in studies of poverty, inequality, growth and convergence. Hence, the bias alters the findings of these studies. This paper estimates both the bias and the subsequent consequences for estimates of inequality and convergence. The findings are that international income inequality tends to be underestimated whereas the convergence between poor and rich countries tends to be overestimated when analyses are based on the Penn World Table. The biases in the macro price variables are caused by factors analogous to those that create bias in consumer price indices. Exploiting this feature, the bias in the cross country comparable macro prices is measured by comparing estimated Engel curves for food, a method already established in measuring biases in consumer price indices.

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Section: Main Model Based On Household Surveyscontrasting

confidence: 59%

Section: Explaining the Biasmentioning

confidence: 99%

International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food

Almås

2007

SSRN Journal

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“…We combine the rural food prices in the survey data with urban food prices from the China Price Statistical Yearbook (2003), 13 which we in turn combine with non-food prices from the China Price Statistical Yearbook (1992) 14 ; see Appendix C for details. Although the relative price measure is calculated from a price set that represents only a subset of both food and non-food consumption, this provides us with a proxy for relative prices.…”

Section: Relative Pricesmentioning

confidence: 99%

Econometric Regime Shifts and the US Subprime Bubble

Anundsen

2012

SSRN Journal

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China's economic development in recent decades has been tremendous, but subject to debate. This paper calculates regional prices that make incomes comparable across both time and space using the Engel-curve approach. Incomes are adjusted using these price indices, providing new estimates of inequality and poverty development. Our findings contrast with measures based on the official consumer price indices (CPIs) -in a time characterized by high economic growth, we find a larger increase in inequality and a more moderate poverty reduction than what is indicated by the CPI-adjusted measures.

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“…The Boskin Commission and several other surveys have estimated CPI bias by assembling direct bias estimates for parts of the index from a variety of sources. Costa (2001) and Hamilton (2001) use an alternative approach that essentially determines how much CPI-U adjusted income needs to be further adjusted so that spending patterns at adjusted income are unchanged over time. Costa (2001) All of these sources indicate that the upward bias in the CPI-U exceeds the 0.4 -0.5 percentage points per year correction of the CPI-U-RS.…”

Section: Price Indicesmentioning

confidence: 99%

Five Decades of Consumption and Income Poverty

Meyer¹,

Sullivan²

2009

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This paper examines poverty in the United States from 1960 through 2005. We investigate how poverty rates and poverty gaps have changed over time, explore how these trends differ across family types, contrast these trends for several different income and consumption measures of poverty, and consider explanations for the differences in trends. We document sharp differences, particularly in recent years, between different income poverty measures, and between income and consumption poverty rates and gaps. Moving from the official pre-tax money income measure to a disposable income measure that incorporates taxes and transfers has a substantial effect on poverty rate changes over the past two decades. Furthermore, consumption poverty rates often indicate large declines, even in recent years when income poverty rates have risen. We show that bias in the CPI-U has a sizable effect on changes in poverty. Between the early 1960s and 2005, an income poverty measure that corrects for bias in this price index declines by 14 percentage points more than a comparable measure based on the CPI-U. The patterns are very different across family types, with consumption poverty falling much faster than income poverty for single parents and the elderly, but more slowly for married couples with children. Income and consumption measures of deep poverty and poverty gaps have generally moved sharply in opposite directions in the last two decades with income deep poverty and poverty gaps rising, but consumption deep poverty and poverty gaps falling. While relative poverty rose in the early 1980s, changes in relative poverty have been fairly small since 1990. We examine the role that demographics, taxes, and transfers play in explaining changes in poverty over the past three decades. We also consider whether measurement error, saving and dissaving, and other explanations can account for income and consumption differences.

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Estimating Real Income in the United States from 1888 to 1994: Correcting CPI Bias Using Engel Curves

Cited by 137 publications

References 10 publications

International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food

International Income Inequality: Measuring PPP Bias by Estimating Engel Curves for Food

Econometric Regime Shifts and the US Subprime Bubble

Five Decades of Consumption and Income Poverty

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