Measurement Error In Income Research Articles

Changes in health-related quality of life: a compensating income variation approach

ABSTRACTThis paper investigates the relationship between negative changes in health and life satisfaction, using a sample from the Household, Income and Labour Dynamics of Australia Survey. We use panel data models and estimate the life satisfaction impact of several different changes in health status to calculate the Compensating Income Variation (CIV) of them. Our work innovates with respect to the existing literature by using a more robust CIV method that takes account of the potential measurement error in income. Further, we produce the first set of monetary values for health losses using SF-6D utility values, one of the main measures used to estimate and value health change for economic evaluation. We show that negative changes in SF-6D are significantly associated with a reduction in life satisfaction, and the starting point matters: a drop of 0.1 in SF-6D score is associated with a decrease of 0.12 points in life satisfaction if the starting utility value is 0.8, but the effect is 100% higher if the SF-6D starting point is 0.7. More generally, we find that a 0.1 deterioration in SF-6D has a strong association with life satisfaction and that the CIV value is substantial (over US$ 120,000).

Measurement Error in Income and Schooling and the Bias of Linear Estimators

We propose a general framework for determining the extent of measurement error bias in ordinary least squares and instrumental variable (IV) estimators of linear models while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing and Retirement in Europe data with Danish administrative registers. Contrary to most validation studies, we find that measurement error in income is classical once we account for imperfect validation data. We find nonclassical measurement error in schooling, causing a 38% amplification bias in IV estimators of the returns, with important implications for the program evaluation literature.

Intergenerational Mobility in Income and Economic Status in Ethiopia

Using data from two comprehensive national labour force surveys conducted in 2005 and 2013, this paper examines the extent of intergenerational mobility in Ethiopia using monetary and non-monetary measures. Quantile regression and OLS based results suggest there is moderate level of stickiness in income mobility across generations. Sons are found to be more mobile than daughters both in monetary and non-monetary terms, although the mobility gap appears to have narrowed recently. There is virtually no evidence on intergenerational mobility in the context of low income countries in general and Sub-Saharan Africa in particular. The paper thus provides valuable insights into issues of intergenerational mobility in a low income country setting. The mixed approach used addresses possible measurement error in income, as well as offering a broader scope in examining intergenerational mobility.

Measurement Error in Income and Schooling, and the Bias of Linear Estimators

The characteristics of measurement error determine the bias of linear estimators. We propose a method for validating economic survey data allowing for measurement error in the validation source, and we apply this method by validating Survey of Health, Ageing and Retirement in Europe (SHARE) data with Danish administrative registers. We find that measurement error in surveys is classical for annual gross income but non-classical for years of schooling, causing a 21% amplification bias in IV estimators of returns to schooling. Using a 1958 Danish schooling reform, we contextualize our result with an estimate of the income returns to schooling.

Winning the War: Poverty from the Great Society to the Great Recession

We consider the long-run patterns of poverty in the United States from the early 1960s to 2010. Our results contradict previous studies that have argued that poverty has shown little improvement over time or that antipoverty efforts have been ineffective. We find that moving from traditional income-based measures of poverty to a consumption-based measure and, crucially, adjusting for bias in price indexes lead to the conclusion that the poverty rate declined by 26.4 percentage points between 1960 and 2010, 8.5 percentage points of which has occurred since 1980. Our consumption-based measure suggests considerably greater improvement than the income-based measures for single-parent families and the elderly, but relatively less for married-parent families. Changes in tax policy explain a substantial part of the decline in poverty; Social Security has also been important, but other transfer programs have played a small role. Changes in education have also contributed, but other demographic trends have had little impact. Measurement error in income likely explains some of the most noticeable differences between changes in income poverty and in consumption poverty, but saving and dissaving appear to play a modest role for most demographic groups.

How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam

Research on economic growth and inequality inevitably raise issues concerning economic mobility because the relationship between long-run inequality and short-run inequality is mediated by income mobility; for a given level of short-run inequality greater mobility implies lower long-run inequality. Yet empirical measures of both inequality and mobility are biased upward due to measurement error in income and expenditure data collected from household surveys. This paper presents a straightforward method to remove this bias using instrumental variable estimates. The method is applied to panel data from Vietnam. The results imply that at least 15%, and perhaps as much as 42%, of measured mobility is upward bias due to measurement error. The results also suggest that measurement error accounts for at least 12% of measured inequality.

The relationship between income and health using longitudinal data from New Zealand

BackgroundEvidence for a cross-sectional relationship between income and health is strong but is probably biased by substantial confounding. Longitudinal data with repeated income and health measures on the same individuals...

Measurement Error and Its Impact on Estimates of Income and Consumption Dynamics

This paper uses data from the Korean Labor and Income Panel Study (KLIPS) to examine whether measurement error in income and consumption has the potential to generate biases for studies on income and consumption dynamics. A first-differenced dynamic panel model is estimated with lagged income and consumption as internal instruments and the household head's satisfaction with their household income as an external instrument. This study suggests that there is substantial time-varying measurement error in reported income and consumption, leading to a bias towards zero in the estimates of income and consumption dynamics. Time-invariant measurement error and unobserved heterogeneity are also found to be important and to lead to upward biases in the estimated coefficients, offsetting the effect of time-varying measurement error. The standard deviation of time-varying measurement error is as large as the standard deviation of the equation error for both income and consumption dynamics. This result also supports the view that time-varying measurement error exists in reported income and consumption and has a substantial magnitude.Interestingly, the standard deviation of time-varying measurement error, as well as that of the equation error, is much larger in the model for the income dynamics than that for consumption dynamics. This result suggests that time-varying measurement error is more prevalent and varies more across households in income than in consumption and also indicates that households smooth their consumption relative to their income in the face of shocks.

The Persistence of Income Shocks: Evidence from Rural Indonesia

AbstractThis paper estimates the persistence of transient income shocks to farm households in rural Indonesia. Persistence is defined as the elasticity of a household's 1997 household per capita income with respect to its 1993 per capita income, controlling for time‐invariant characteristics of the household. Local rainfall levels are used as an exogenous source of transitory variation in 1993 income. Four main conclusions emerge. First, roughly 30% of household income shocks remain after four years. Second, the persistence of negative and positive shocks is approximately equal; if anything, positive shocks last longer. Third, neither positive nor negative income shocks disproportionately affect poor households. Finally, measurement error in income and unobserved household heterogeneity are important sources of bias. These findings cast doubt on common arguments advocating public intervention to stabilize or redistribute income, and suggest that anti‐poverty policy should address more permanent causes of household poverty.

Daddies, Devotion, and Dollars

Abstract. Growing up in a family that lacks a biological father is correlated with a number of poor outcomes for youths. This study uses the National Educational Longitudinal Survey of 1988 to examine the extent to which differences in income or parental involvement can explain the effects of family structure on youth outcomes. We find that measurement error in income from single‐parent homes has a large effect on the results because of the variability in income earned over a youth's teen years. Overall, we find that lower income explains most of the disadvantages of youths in single‐parent homes, but neither gaps in income nor in parental involvement explain the disadvantages of families with stepfathers.

Life-Cycle Effects on Household Expenditures: A Latent-Variable Approach

Using data from the Spanish household budget survey, we investigate life-cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

Testing the Response of Consumption to Income Changes with (Noisy) Panel Data

This paper tests the rational expectations lifecycle model of consumption against (i) a Keynesian model and (ii) the rational expectations lifecycle model with imperfect capital markets. The tests are based upon the relative responsiveness of consumption to income changes that can be predicted from past information and income changes that cannot he predicted. The tests allow for measurement error in income. The results reject the Keynesian model and generally support the lifecycle model. But the results are not sufficiently precise to rule out the possibility that some households are liquidity constrained. Measurement error has a strong influence on the relationship between consumption and income.