Federal Reserve Bank of Minneapolis: 'Family & Government Insurance – Wage, Earnings, Income Risks in Netherlands, U.S.'

MINNEAPOLIS, Minnesota, Oct. 27 -- The Federal Reserve Bank of Minneapolis Opportunity and Inclusive Growth Institute issued the following working paper (No. 42) entitled "Family and Government Insurance: Wage, Earnings, and Income Risks in the Netherlands and the U.S."

The paper was co-authored by Mariacristina De Nardi, consultant for the Opportunity and Inclusive Growth Institute, CEPR, and NBER, Giulio Fella of Queen Mary University of London, CFM, and IFS, Marike Knoef of Leiden University and Netspar, Gonzalo Paz-Pardo of the European Central Bank and Raun Van Ooijen of the University of Groningen, University Medical Center Groningen, and Netspar.

Here are the excerpts:

Abstract

We document new facts about risk in male wages and earnings, household earnings, and pre- and post-tax income in the Netherlands and the United States. We find that, in both countries, earnings display important deviations from the typical assumptions of linearity and normality. Individual-level male wage and earnings risk is relatively high at the beginning and end of the working life, and for those in the lower and upper parts of the income distribution. Hours are the main driver of the negative skewness and, to a lesser extent, the high kurtosis of earnings changes. Even though we find no evidence of added-worker effects, the presence of spousal earnings reduces the variability of household income compared to that of male earnings. In the Netherlands, government transfers are a major source of insurance, substantially reducing the standard deviation, negative skewness, and kurtosis of income changes. In the U.S. the role of family insurance is much larger than in the Netherlands. Family and government insurance reduce, but do not eliminate nonlinearities in household disposable income by age and previous earnings in either country.

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Introduction

Wage risk affects key economic decisions, including consumption, saving, and labor supply, and is an important determinant of household's welfare. Households can self-insure against wage shocks: single people can adjust their own labor supply and savings and couples can adjust the labor supply of both partners, in addition to savings. Furthermore, governments can supplement or partly replace the need for self-insurance through progressive taxes and transfers.

This paper studies the distribution of wage shocks and the role of insurance mechanisms against them in the Netherlands and the Unites States. We start by documenting the distribution of wage shocks at the individual level by analyzing distributional measures of wage changes, including the standard deviation, skewness, kurtosis, and persistence, by age and previous earnings. To understand the role of individual-level labor supply and fluctuations in hours, we compare the distribution of individual wage shocks with that of individual-level earnings. To analyze the role of family insurance through the labor supply of both partners, we compare the distributions of individual-level and household-level earnings. To examine the role of government insurance, we compare the distribution of household income, pre- and post-taxes, and transfers, by age group and previous earnings.

We use administrative data on income, taxes, and government transfers on individuals and households for the Netherlands (IPO) to get precise estimates of the dynamics of wage shocks and the role of private and public insurance mechanism to mitigate these shocks. We compare the results with estimates for the U.S. Panel Study of Income Dynamics (PSID), and find that the distribution of wage and earnings shocks display rich dynamics and, particularly, depend on age and previous earnings in both countries, as was previously documented for earnings in the U.S. (Guvenen, Karahan, Ozkan and Song, 2015, and Arellano, Blundell and Bonhomme, 2017).

Our contribution to the literature is threefold. First, whereas most previous studies investigated shocks to individual earnings, we distinguish between changes in wages and changes in hours worked. As the two may have different dynamics, this provides us with a better understanding of the nature of income risk. Using high-quality Dutch administrative data on hours worked derived from payroll administration, we find that hours are the main driver of the variability at the bottom of the earnings distribution, the negative skewness and, to a lesser extent, the high kurtosis of earnings. This differs from what we find in Dutch household survey data (DNB Household Survey) or the PSID, and suggests that accurate measurement of earnings and hours worked is crucial to properly account for wage dynamics.

Second, we investigate the degree of insurance provided by spousal labor supply and by the tax and transfer system. We find that the family is a relevant source of insurance in the Netherlands, but most of this insurance comes from income pooling rather than labor supply reactions of secondary earners or added worker effects. Taxes and, particularly, the transfer system play an even larger role in reducing income risk.

Third, we compare two countries: the Netherlands and the U.S. This is an interesting comparison because these two countries differ substantially in the size of their welfare state and the progressiveness of their tax system./1

We find that family insurance is more relevant in the U.S. than in the Netherlands, whilst in the latter the government is responsible for the bulk of the reduction in income risk. This also holds if we compare survey data across both countries. Finally, our analysis provides data that rich models of risks and insurance should match to be consistent with the key features of the micro-data that we document.

Our paper contributes to a growing literature on higher-order moments of income shocks. Guvenen et al. (2015) investigate higher order earnings risk using US Social Security administrative data. They find substantial nonlinearities and non-normalities, but they can only study gross individual earnings process, so they cannot separate hours and wages or study additional insurance mechanisms. Hoffman and Malacrino (2019) use Italian administrative data to decompose earnings growth in changes in employment time and changes in weekly earnings. Like us, they find that changes in employment time are the main driver of earnings growth. Halvorsen, Holter, Ozkan and Storesletten (2019) analyze Norwegian data and attribute changes in earnings mostly to changes in wages. These international differences suggest that country-specific institutional features are important to determine whether wages or hours are the most important margin of adjustment. Similarly to our results, Halvorsen et al. (2019) find that the benefit system is particularly important to insure workers against earnings fluctuations. Pruitt and Turner (2018), use administrative data from the U.S. and find that the probability of the secondary earner entering employment rises when the primary earner experiences earnings losses.

There is mounting interest in the higher-order moments of income shocks. They are key input for models on asset prices (Mankiw, 1986; Constantinides and Ghosh, 2017; Schmidt, 2016), monetary policy (Kaplan, Moll and Violante, 2018), and optimal social insurance and taxation (Golosov, Troshkin and Tsyvinski, 2016). Taking into account higher-order moments also influence estimates on the welfare costs of earnings fluctuations (De Nardi, Fella and Paz-Pardo (2019) find that they are smaller when taking into account higher-order moments).

These rich features derive from important economic mechanisms (Postel-Vinay and Turon (2010) and Graber and Lise (2015)). For instance, a job ladder model can explain negative skewness and some kurtosis because most people stay on the job and experience small wage raises, while a small number of people lose their job and face large wage and earnings drops. In addition, the persistence of these wage changes might depend on one's age (a young worker is more likely to experiment and switch jobs to figure out what he or she is best at) while an old worker might switch to a part-time or less demanding job.

The remainder of the paper proceeds as follows. Section 2 describes our data and approach, Sections 3 and 4 present the results and Section 5 concludes.

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Conclusions

We study the nature of labor income risk in the Netherlands and the U.S. For the Netherlands, we use high-quality administrative data to disentangle the contribution of wages and hours to the dynamics of male earnings. Furthermore, we investigate the degree of insurance provided by spousal labor supply and by the tax and transfers system in both countries.

We document that the dynamics of individual male earnings is similar in both countries and displays important deviations from the typical assumptions of linearity and normality. Individual-level male wage and earnings risk is relatively high at the beginning and end of the working life, and for those in the lower and upper parts of the income distribution. Importantly, we find that hours are the main driver of the negative skewness and, to a lesser extent, the high kurtosis of earnings changes. In the Netherlands, hours also account for most of the variability of earnings for workers in the bottom two deciles of the earnings distribution.

Turning to family and government insurance, in the Netherlands women's earnings reduce the standard deviation of labor income risk at the household level only if the husband's earnings are in the bottom third of the earnings distribution. Indeed, for the age group 25-34 the variance of household earnings exceeds that of the husband's earnings if the latter are in the top two-thirds of the distribution. This is probably due to the birth of children. However, income pooling within the household makes skewness substantially less negative, thus suggesting that the presence of a secondary earner in the household can smooth out large negative shocks. This effects appear stemming from income pooling alone, as we do not find evidence of an added worker effect in the Netherlands.

Comparing family and government insurance we find that the government plays a much larger role in reducing wage risk in the Netherlands compared with the U.S. A breakdown in government programs for older workers in the Netherlands shows that DI and UI programs reduce income risk, especially for the lowest quarter of the male earnings distribution. Pensions and taxes (to a lower extent) reduce earnings risk across the whole distribution. Instead, in the U.S. the role that the family plays is much more important. The results suggest that taxes and transfers may crowd out insurance that could be generated within the family.

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References

Arellano, Manuel, Blundell, Richard and Bonhomme, St'ephane (2017), 'Earnings and consumption dynamics: A non-linear panel data framework', Econometrica 85(3), 693-734.

Busch, Christopher, Domeij, David, Guvenen, Fatih and Madera, Rocio (2018), Asymmetric business-cycle risk and social insurance, Working Paper 24569, National Bureau of Economic Research.

Constantinides, George M. and Ghosh, Anisha (2017), 'Asset pricing with countercyclical household consumption risk', The Journal of Finance 72(1), 415-460.

De Nardi, Mariacristina, Fella, Giulio and Paz-Pardo, Gonzalo (2019), 'Nonlinear Household Earnings Dynamics, Self-Insurance, and Welfare', Journal of the European Economic Association 18(2), 890-926.

Golosov, Mikhail, Troshkin, Maxim and Tsyvinski (2016), 'Redistribution and social insurance', American Economic Review 106, 359-386.

Graber, Michael and Lise, Jeremy (2015), 'Labor market frictions, human capital accumulation and consumption inequality', mimeo, University College London.

Guvenen, Fatih, Karahan, Fatih, Ozkan, Serdar and Song, Jae (2015), What do data on millions of U.S. workers reveal about life-cycle earnings risk?, Working Paper 20913, National Bureau of Economic Research.

Halvorsen, Elin, Holter, Hans, Ozkan, Srdar and Storesletten, Kjetil (2019), Dissecting idyosincrtaic income risk. Mimeo.

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Heathcote, Jonathan, Storesletten, Kjetil and Violante, Giovanni L (2014), 'Consumption and labor supply with partial insurance: An analytical framework', American Economic Review 104(7), 2075-2126.

Hoffman, Eran B. and Malacrino, Davide (2019), 'Employment time and the cyclicality of earnings growth', Journal of Public Economics 169, 160-171.

Kalwij, Adriaan, Kapteyn, Arie and de Vos, Klaas (2018), Why Are People Working Longer in the Netherlands?, University of Chicago Press, pp. 179-204.

Kaplan, Greg, Moll, Benjamin and Violante, Giovanni L. (2018), 'Monetary policy according to hank', American Economic Review 108(3), 697-743.

Karahan, Faith and Ozkan, Serdar (2013), 'On the persistence of income shocks over the life cycle: Evidence, theory and implications', Review of Economic Dynamics 16(3), 452-476.

Mankiw, N. Gregory (1986), 'The equity premium and the concentration of aggregate shocks', Journal of Finance Economics 17, 211-219.

Postel-Vinay, Fabien and Turon, H'el`ene (2010), 'On-the-job search, productivity shocks, and the individual earnings process', International Economic Review 51(3), 599-629.

Pruitt, Seth. and Turner, Nick (2018), The nature of household labor income risk. Finance and Economics Discussion series working paper 2018-034.

Schmidt, Lawrence (2016), Climbing and falling of the ladder: asset pricing implications of labor market event risk. Working paper, University of Chicago.

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REPORT and FOOTNOTES: https://www.minneapolisfed.org/institute/working-papers-institute/iwp42.pdf