How Does Public Sector Employment Affect Household Saving Rates? Evidence from China

Layer 1: Overview

Research question and motivation: The paper asks whether and why the type of employment — specifically public-sector employment — affects household saving rates in China. This matters because Chinese household saving rates are extraordinarily high in international comparison (the paper reports an average gross household saving rate of roughly 35% in China versus only about 5% in OECD countries over the period considered), and the high rates remain a puzzle. Household saving feeds investment and long-run growth, its cyclicality can amplify or dampen crises, and via the “global saving glut” hypothesis Chinese saving has financed global imbalances and the US current account deficit. Prior literature on Chinese saving emphasizes economic transition, income growth/uncertainty, demographics (one-child policy), and culture, but neglects the role of employment type. Notably, the international finding (e.g., Bettoni and Santos, 2021, calibrated on Brazilian data) is that public employment REDUCES saving because of lower job/income uncertainty and higher compensation, so less precautionary saving. China appears to run the opposite way.

Data and strategy: Micro-level longitudinal data from the China Household Finance Survey (CHFS), a nationally representative survey covering 29 provinces (excludes Tibet, Xinjiang, Inner Mongolia). The authors use the 2013, 2015, and 2017 waves, restrict to urban households whose head is aged 16-60, and restrict the non-public control group to those with an above-one-year labor contract. The final sample is 5,539, 5,785, and 4,545 observations per wave (15,869 total; 25.18% public-employed). The saving rate is defined as (income minus consumption)/income, with the sample restricted to saving rates above -200% to remove extreme values. Crucially, SOE employees are classified as NON-public (following You and Zhang, 2016) because post-1990s SOE reform made them market players. Public employees = government workers (about 20% of public employees) plus Shiyedanwei (fiscally-financed public institutions: education, health, research). The empirical toolkit: (1) Correlated Random Effects (CRE) panel regressions with rich controls, plus IV-CRE using the head’s CPC membership as instrument; (2) Propensity Score Matching (one-to-one, k-nearest neighbor, radius, kernel) and a PSM-CRE panel model; (3) Heckman two-step treatment-effects model for self-selection; (4) a within-household differences estimator exploiting employment transitions; (5) life-cycle interaction analysis.

Main quantitative findings: Public-employed households save more, by roughly 3 to 8 percentage points depending on method and sample. Raw descriptive gap: mean/median saving rates are 23.16%/33.89% for public vs. about 5.6 and 4.8 pp lower for non-public. Baseline CRE: the public-employment dummy adds 3.589 pp (col 1); each additional public-employed member adds 2.028 pp (col 3). IV-CRE coefficients rise to 8.094 and 4.878 (significant only at 10%; first-stage F = 38.65 and 49.68). PSM cross-sectional ATEs are about 5-8 pp (mostly significant at 1%). PSM-CRE: 3.928 pp. Heckman: 3.557 pp, with an insignificant inverse Mills ratio (so self-selection is not driving the result). Employment-transition (within-household): households switching from non-public to public raise their saving rate by 14.245 pp relative to non-switchers (135 transitioning vs. 1,831 stable households). Life-cycle: the public-employment x age interaction is negative; the saving-rate gap is significant for heads roughly aged 24-38 (strongest for the young/middle-aged), with a U-shaped age-saving profile turning around age 35-40. Robustness on the definition of “public”: holding Bianzhi raises saving by 8.5 pp; broadening to include SOEs gives 4.5 pp.

Mechanisms and implications: The saving rate reflects both motive and capacity. On motives, public-employed households save more for children’s education (about 25% report saving for education/training vs. 19% non-public; 16.2% plan to send children to study abroad vs. 12.9%) and inheritance (about 16% vs. 11.4%); heterogeneity shows the effect is concentrated in one-SON households (Wei-Zhang competitive saving) and in households with high education-expense shares. On capacity, better social security coverage reduces public employees’ out-of-pocket expenditure needs (e.g., negative food-income interaction) and frees disposable income for saving; social-security interaction terms are negative, indicating public employment’s effect is dampened where social security is already held. Policy implication: changes to the public-employment share affect aggregate household saving, and reducing the benefit/guarantee disparity between public and non-public jobs could lower the high saving of public-employed households. Scope: results are Chinese institution- and culture-specific, possibly extendable to other East Asian Confucian societies, and may erode as ongoing public-sector reforms cut public employees’ benefits.

Layer 2: Deep Dive

What is the core empirical claim and how large is the effect?

Households headed by a public employee have higher saving rates than non-public-employed households, by approximately 3 to 8 percentage points depending on method and sample. Point estimates: baseline CRE 3.589 pp (dummy) and 2.028 pp per additional public-employed member; PSM-CRE 3.928 pp; Heckman 3.557 pp; PSM cross-sectional ATEs about 5-8 pp; IV-CRE 8.094/4.878 pp (only 10% significant).

What is the identification strategy and what are the main threats?

Three threats are addressed: (1) confounders affecting both employment choice and saving (education, risk aversion, financial literacy, social security) — handled with rich CRE controls; (2) endogeneity/reverse causality (households with strong saving desire may sort into a sector) — handled with IV using the head’s CPC membership; (3) self-selection into public jobs — handled with PSM and a Heckman two-step treatment-effects model. The within-household employment-transition estimator further nets out fixed household characteristics. Main residual threat: the IV’s exclusion restriction cannot be formally tested (just-identified, instruments do not exceed endogenous variables); the authors argue CPC membership is plausibly excludable since many students join the CPC before graduation and many CPC members work in the private sector. The Heckman IMR is insignificant, indicating self-selection is not the driver.

Why is the instrument (CPC membership) argued to be valid?

Relevance: about 3 in 10 public employees are CPC members vs. 1 in 10 private employees; first-stage F-statistics are 38.65 and 49.68, well above weak-instrument thresholds. Exogeneity (argued, not tested): no direct channel from CPC membership to saving decisions because many college students join the CPC and many members work in private sectors. The orthogonality (third) condition cannot be tested due to just-identification.

What are the two main mechanisms, and how are they distinguished?

Saving motive and saving capacity. Motive: from the 2013 CHFS bank-deposit-purpose question and study-abroad plans, public-employed households more often save for children’s education (about 25% vs. 19%), inheritance (about 16% vs. 11.4%), health (10.25% vs. 8.49%), and housing (15% vs. 13.78%). Capacity: better social security reduces expenditure needs and frees disposable income — shown by consumption regressions (negative public-employment x income interaction for food, positive for education/travel/luxury) and by social-security interaction terms that are negative and by smaller public-employment coefficients in the with-social-security subsample. The two are distinguished by combining stated-motive data with consumption-category and social-security interaction analyses.

What heterogeneity is documented?

(1) Life-cycle: the saving gap is significant and strongest for heads aged about 24-38 (young/middle-aged) and narrows with age; the public-employment x age interaction is negative. (2) Child gender: the positive effect comes primarily from one-SON households (one-son public coefficient 6.067 significant; one-daughter insignificant; interaction with son gender 5.872), consistent with Wei-Zhang competitive/marriage-market saving. (3) Education-expense share: the effect is larger for households spending a higher share on children’s education (above-median 7.536 vs. below-median 4.471). (4) Definition of public sector: Bianzhi holders 8.5 pp; including SOEs 4.5 pp.

What robustness checks are run?

(1) IV-CRE to address endogeneity. (2) Alternative saving-rate measures: winsorizing at the bottom 1% instead of the -200% cutoff, and a log(income)-log(consumption) definition (saving relative to consumption); the positive effect holds (CRE 0.043, PSM-CRE 0.243). (3) Alternative thresholds (-100%, -300%) give similar results. (4) Different scopes of ‘public sector’ (Bianzhi-only narrow; SOE-inclusive broad). (5) Regressing each saving-motive dummy on public employment plus controls to avoid being misled by raw means. (6) Number-of-public-members measure as an alternative to the head dummy. (7) Multicollinearity checked via correlation matrix; regressions without singletons reportedly robust.

How does this paper relate to and differ from closely related prior work?

It contrasts directly with Bettoni and Santos (2021), who (using Brazilian micro data) find public employment LOWERS saving via reduced precautionary motive. This paper finds the opposite for China and argues the precautionary channel is only part of the story; Chinese-specific cultural factors (Confucian social status, competitive saving for sons, status investment in children) and capacity effects (better social security freeing disposable income) dominate. It complements He et al. (2018), who use SOE reform to document precautionary saving, and Lugauer et al. (2019) and Chen et al. (2019) on dependent children and social norms. Methodologically it extends the Chinese saving literature by foregrounding employment type, a political/occupational dimension prior work largely neglected.

What does the employment-transition (within-household) result show and what is its caveat?

Households whose head switches from non-public to public employment raise their saving rate by 14.245 pp relative to non-public households without a transition. This nets out time-invariant household characteristics, supporting causality. Caveat: the transition sample is small (135 transitioning households vs. 1,831 stable), and the coefficient is much larger than cross-sectional estimates, so it should be read as directional confirmation rather than a precise magnitude.

What are the policy implications and their scope conditions?

Changes in the public-employment share will affect aggregate household-sector saving; policymakers wishing to lower China’s high saving could reduce the benefit/guarantee disparity between public and non-public jobs. Scope conditions: results are specific to Chinese institutions and Confucian culture, may extend to other East Asian societies, and may weaken over time as ongoing public-sector reforms cut public employees’ benefits, shrinking the public/non-public gap.

What are the stated limitations?

(1) External validity is limited by Chinese-specific institutional and cultural settings, though possibly applicable to similar East Asian cultures. (2) Ongoing reduction of public employees’ benefits through public-administration reform may change saving behavior and reduce the documented gap over time. The dataset also covers only employed heads aged 16-60, so it does not capture post-retirement saving behavior.

What do the control variables show?

Higher household assets reduce the saving rate; higher income percentiles raise it (monotonically); male-headed households save more; a U-shaped age profile (low around middle age 35-40); high-school education lowers saving while university education is insignificant; larger household size, being married, and more dependent children all reduce saving; risk aversion raises saving while risk-loving and financial literacy are insignificant. In the Heckman first-stage probit, higher education, CPC membership, and risk aversion raise the probability of public employment, and the mother’s (not father’s) education and CPC membership significantly predict the head’s public employment.

Key Concepts

Public employee (paper’s definition): In this paper, employees who work directly for central/local government (about 20% of public employees) plus those in Shiyedanwei (fiscally-financed public institutions such as education, health, and research). SOE employees are deliberately EXCLUDED and classified as non-public, because post-1990s SOE reform made them resemble market players rather than public-sector actors.

Shiyedanwei: Public institutions and state organs mainly financed by fiscal spending (e.g., schools, hospitals, research institutes). Their staff are counted as public employees in this study, with relatively low unemployment risk and higher compensation.

Bianzhi: The authorized number of established posts/personnel in government and its affiliated institutions (per Brodsgaard, 2002). Employees holding Bianzhi are fully fiscally dependent — employment and wage guaranteed by the government — and thus the most secure subgroup of public employees; their saving-rate premium is the largest (8.5 pp).

Saving capacity vs. saving motive: The paper’s framing that a household’s saving rate is jointly determined by the desire to save (motive: education, inheritance, status) and the ability to save (capacity: how much disposable income is freed after needs, raised by better social security that lowers expenditure needs).

Iron rice bowl: The pre-reform notion of guaranteed lifetime job security in state employment; invoked to explain why public-sector jobs in China historically carried very low unemployment risk, a status partially eroded by SOE reform for SOE workers (but retained by core public employees).

Correlated Random Effects (CRE) model: A Mundlak (1978) random-effects specification that adds time-averages of time-varying regressors, allowing correlation between explanatory variables and the unobserved individual effect; chosen over fixed effects because employment type varies little within households across waves.

Competitive saving motive: The Wei-Zhang (2011) idea that households with a son save more to improve his marriage-market competitiveness amid China’s high male sex ratio. The paper finds this motive is concentrated among public-employed one-son households.