Working More to Pay the Mortgage: Zator (2025)

What this is. The paper’s core results, the identification strategies, and the key estimating equations: enough to know what it found and how, without reading all 37 pages. To replicate or extend it, read the full source at 10.1111/jofi.13413.

TL;DR

Using a panel of Polish income tax records linked to floating-rate mortgage interest deductions (2005-2015), Zator shows that households increase their gross labor income by roughly PLN 0.35 for each PLN 1 increase in mortgage interest payments. The effect is causal: identification exploits within-household variation in mortgage size interacted with the reference rate (WIBOR or LIBOR), instrumented to remove endogenous prepayment. The response is sizable and asymmetric: households react two to three times more strongly to payment increases than to decreases. Secondary earners (often women) and dual-earner childless households drive the increase response, consistent with the fixed costs of entering the labor market and consumption commitment models.

Core results

Magnitudes and significance are as reported; \*\*\* = 1%, \*\* = 5%. Locators point into the source PDF.

#	Result	Locator	Magnitude
R1	Labor income rises PLN 0.30-0.35 for each PLN 1 increase in mortgage interest (OLS)	Table III, p. 1185	Coefficients 0.337 to 0.348*** (mortgage holders, cols 1-3); 0.297*** (full population, col 4); se 0.020-0.021
R2	IV estimates confirm OLS: PLN 0.35-0.46 response; reference-rate x mortgage-size instrument	Table III, p. 1185	IV col 5 (mortgage holders): 0.459*** (se 0.043); IV col 6 (full pop): 0.348*** (se 0.037); OLS and IV confidence intervals overlap
R3	Currency-comparison design (PLN vs CHF loans) gives a smaller estimate of PLN 0.15, consistent with asymmetry	Table IV, p. 1188	IV cols 4-5: 0.148*** (se 0.034) mortgage holders, 0.145*** (se 0.016) all; smaller because the CHF/WIBOR divergence covers only the declining-rate 2013-2015 period
R4	Response to payment increases is 2-3x larger than to decreases (asymmetric labor supply)	Table V, p. 1192; Figure 3, p. 1193	Average coefficient 0.106-0.283***; interaction on increases 0.233*** to 0.313*** (six specs); slope for increases roughly 2-3x slope for decreases across all six specifications
R5	Dual-earner households and secondary (often female) earners drive the increase response; women show more pronounced asymmetry	Figure 6, p. 1198; Figure 7, p. 1199	Dual-earner coefficient on payment increase ~0.48 vs single-earner ~0.14; secondary earner coefficient substantially higher than primary on increases; women increase income strongly on increases but do not reduce significantly on decreases
R6	Higher mortgage payments reduce the probability of remaining a single-earner household by 0.1 pp per PLN 1,000	Table VI, col 4, p. 1201	Coefficient -0.113*** (se 0.021); mean dep var 27.5%; consistent with spousal labor market entry as a key mechanism
R7	Higher mortgage payments raise the probability of changing jobs by 0.104 pp per PLN 1,000	Table VI, col 6, p. 1201	Coefficient 0.104*** (se 0.013); mean dep var 21.9%; consistent with households accepting higher-paying, less-preferred jobs to service debt

Overall (paper’s conclusion). Households with floating-rate mortgages adjust their labor supply substantially in response to interest rate changes. Income adjusts by roughly 35% of the payment change on average, with a markedly stronger response to increases. The adjustment operates through spousal labor market entry, supplemental gig income, and job changes toward higher-paying positions. The asymmetry helps reconcile the wide dispersion of labor supply elasticity estimates in the literature: lottery-win studies such as Imbens, Rubin, and Sacerdote (2001) and Cesarini et al. (2017) capture responses to budget-loosening shocks (comparable to payment decreases here), while Di Maggio et al. (2017) document consumption responses to ARM resets consistent with the labor supply responses this paper finds. Brown and Matsa (2020) and Bernstein and Koudijs (2020) show correlated patterns in the relationship between household debt and labor market outcomes.

Theory / model

The paper has no formal structural model. It operates from a standard household labor-leisure model in which the household equates the marginal disutility of work with the marginal utility of consumption (p. 1184). When mortgage payments rise, the available budget for non-housing consumption falls, raising the marginal utility of consumption and, under concave utility, inducing greater labor supply. This mechanism implies the response to payment increases should be stronger than to decreases when utility is concave, which is the core theoretical prediction tested in Section IV.

The paper invokes Chetty and Szeidl (2007) to argue that consumption commitments (housing being the canonical commitment) amplify the asymmetry. With a commitment that cannot be adjusted downward quickly, an increase in the committed payment has a large liquidity effect with no offsetting consumption substitution on the downside.

Method

The paper uses two complementary identification strategies, both estimating panel regressions with individual fixed effects and rich controls.

Strategy 1: Reference-rate x Mortgage-size variation (equation (1), p. 1180). The main estimating equation is:

$$Y_{i,t} = \alpha \cdot (\text{Interest}_{i,t} = \text{RefRate}_t \cdot \text{LoanSize}_i) + \mu_i + \xi X_{i,t} + \epsilon_{i,t} \tag{1}$$

where $Y_{i,t}$ is gross household income for person $i$ in year $t$, $\text{Interest}_{i,t}$ is annual mortgage interest deducted from taxable income, $\mu_i$ is an individual fixed effect, and $X_{i,t}$ includes year-by-age-by-previous-income bin fixed effects and county-year fixed effects. To remove endogenous variation from prepayment decisions, interest is instrumented with the product of the reference rate (WIBOR for PLN loans, LIBOR CHF for CHF loans) and an estimate of initial mortgage size (the household’s second observed positive interest payment). The instrument is strong (Kleibergen-Paap F-statistics of 5.5-7.6 x 10^4 in Table III, p. 1185).

This approach resembles a shift-share design (Borusyak, Hull, and Jaravel (2022)): the endogenous exposure measure (mortgage size) is interacted with several exogenous shocks (11 years of reference rate changes from two correlated rates). Standard errors are clustered at the household level throughout.

Strategy 2: Currency-comparison design (equation (2), p. 1181). The second design compares PLN-indexed (WIBOR) and CHF-indexed (LIBOR) mortgages of the same size after 2012, when LIBOR hit the zero lower bound while WIBOR continued to decline:

$$Y_{i,t} = \beta \cdot (\text{Interests}_{i,t} = \text{LoanSize}_i \cdot \text{Post2013}_t \cdot \text{PLNLoan}_i) + \phi \cdot \!\!\left(\text{LoanSize}_i \cdot \sum_{t=2006}^{2015} \text{Year}_t\right) + \mu_i + \xi X_{i,t} + \epsilon_{i,t} \tag{2}$$

The coefficient $\beta$ captures the differential income change for PLN-loan households relative to CHF-loan households of the same size after 2013. Since LIBOR was flat and WIBOR declined, this design identifies the labor supply response to payment decreases.

Asymmetry test (equation (3), p. 1182). To test asymmetry, the base specification is augmented with an interaction between the interest payment and a binary indicator for years in which payments increased:

$$Y_{i,t} = \alpha \cdot \text{Interests}_{i,t} + \beta \cdot \text{Interests}_{i,t} \cdot \text{Increase}_{i,t} + \mu_i + \beta X_{i,t} + \epsilon_{i,t} \tag{3}$$

The coefficient $\alpha$ captures the response to payment decreases and $\alpha + \beta$ captures the response to payment increases; Table V (p. 1192) shows $\beta > 0$ and significant across three alternative definitions of the increase indicator.

Empirical specifications

All regressions use a strongly balanced panel with observations weighted by the inverse of household size (one or two). Standard errors are clustered at the household level (or by year for robustness).

First stage (Table II, p. 1185). Reference rate interacted with mortgage size strongly predicts interest payments: coefficient 0.223*** (se 0.001 household-cluster; 0.012 year-cluster) on the full mortgage-holder sample. WIBOR drives PLN-loan interest (0.145**, se 0.053); LIBOR CHF drives CHF-loan interest (0.234***, se 0.041).

Main income regressions (Table III, p. 1185). Specification columns:

• Col 1-3: Mortgage holders, progressively adding previous-income-year FE and county-year FE. Coefficient stable at 0.337-0.348.
• Col 4: Full population (OLS); coefficient 0.297***.
• Col 5-6: IV (instrument = RefRate x LoanSize); coefficient rises slightly to 0.459*** (mortgage holders) and 0.348*** (full population).

Currency-comparison regressions (Table IV, p. 1188). First stage: PLN loan x post-2012 x loan size reduces interest paid by PLN 0.231*** per unit loan size (se 0.010). Second stage income coefficients: 0.148*** and 0.145*** (IV). Pre-2012 coefficients insignificant, confirming parallel trends.

Mechanism regressions (Table VI, p. 1201). Specifications analogous to equation (1) with alternative outcomes: log wages (0.0037***, se 0.0002), log pensions (-0.0001, insig.), log business profits (0.0107***, se 0.0012), single-earner probability (-0.113***, se 0.021 per PLN 1,000), supplemental income indicator (0.013*, se 0.007), job-change indicator (0.104***, se 0.013).

Consumption and savings proxies (Table VII, p. 1203). Interest payments reduce charitable donations (asinh coefficient -0.0012*** to -0.0020***), private pension contributions (-0.0004** to -0.0006***), and internet-access spending (-0.0019*** to -0.0018***), confirming the income response reflects labor supply rather than differential macroeconomic sensitivity of mortgage holders.

Datasets used

Dataset	Role in paper	Wiki page
Polish Ministry of Entrepreneurship and Technology: income tax declarations (PIT), 2005-2015	Universe of Polish taxpayers; individual income sources (wages, business profits, pensions), mortgage interest deductions, demographics (age, sex, county), consumption proxies (charitable donations, pension contributions, internet access)	No page yet
Three-month WIBOR (Warsaw Interbank Offered Rate)	Reference rate for PLN-denominated mortgages; the main shock variable interacted with mortgage size	No page yet
Three-month LIBOR CHF	Reference rate for CHF-denominated mortgages; used in currency-comparison design	No page yet

Sample: Strongly balanced panel, 9.8 million individuals, 2005-2015 annual (100+ million observations). Mortgage-holder subsample: 171,445 individuals (1,714,450 observations). The data are obtained from the Polish government and are not publicly available; replication requires an access agreement with the Polish Ministry of Entrepreneurship and Technology.

When to read the full paper

Use the original if you are: studying the labor supply channel of monetary policy (Section III-IV give the clearest panel IV evidence in a floating-rate mortgage setting); interested in the asymmetry of labor supply responses to income shocks (Section IV and Table V); studying intrahousehold labor supply and the role of secondary earners or women in debt-adjustment (Sections V-VI); or using Poland as a case study for a nearly universal floating-rate mortgage market (99.8% floating rate as of 2016, p. 1176).

Attribution and rights

Source: peer-reviewed, The Journal of Finance 80(2), April 2025, pp. 1171-1207. DOI: 10.1111/jofi.13413. This distillation was extracted by an LLM on 2026-06-06 and is not human-verified or independently reproduced. The article is paywalled; extract-only redistribution.

Zator, Michal. “Working More to Pay the Mortgage: Household Debt, Interest Rates, and Family Labor Supply.” The Journal of Finance 80, no. 2 (April 2025): 1171-1207. DOI: 10.1111/jofi.13413. © 2024 the American Finance Association. This page is an extraction by the Institute for Automated Research: core results summarized with source locators; not a substitute for the original.