Micro Anatomy of Macro Consumption Adjustments: Guntin, Ottonello & Perez (2023)

What this is. The paper’s core results, the model (heterogeneous-agent small open economy with borrowing constraints), and the empirical specifications, with exact source locators. To replicate or extend, read the full source at the original.

TL;DR

This paper documents the cross-sectional patterns of consumption adjustment during five episodes of large aggregate consumption decline: the Euro crisis in Italy and Spain, and three emerging-market sudden stops (Mexico 1994, Mexico 2008, Peru 2008). The central finding is that consumption-income elasticities are near unity across all income groups, including top-income and asset-rich households, contradicting the expectation from credit-tightening theories that wealthy households should smooth consumption. A calibrated heterogeneous-agent open-economy model shows the permanent-income view of crises, in the tradition of Aguiar and Gopinath (2007), can account for the micro-level patterns. Credit-tightening theories, as in Mendoza (2005) and Eggertsson and Krugman (2012), predict a decreasing elasticity pattern across the income distribution that is at odds with the data. The divergence between the two views has direct implications for fiscal transfer policy effectiveness.

Core results

Magnitudes from source tables; locators point into the source PDF.

#	Result	Locator	Magnitude
R1	Average consumption-income elasticity is near 1.0 across all five episodes; large consumption adjustments observed throughout the income distribution	Table 1, Panel A, p. 2209	Average across episodes: 0.92; by episode: Italy 1.13, Spain 0.97, Mexico 1994 0.78, Mexico 2008 0.73, Peru 0.99
R2	Top-income household elasticities are similar to or larger than the economy average; income-rich households do not smooth consumption during these crises	Table 1, Panel A, p. 2209	Top-decile mean: 0.93; by episode: Italy 0.95, Spain 0.90, Mexico 1994 0.79, Mexico 2008 0.88, Peru 1.15
R3	Households holding liquid assets show consumption-income elasticities near the average, ruling out a hand-to-mouth interpretation for the top-income result	Table 1, Panel B, p. 2209	Liquid-asset holders: average elasticity 0.86, top-income elasticity 1.01; defined as holding liquid assets exceeding two weeks of income per Kaplan, Violante, and Weidner (2014)
R4	High consumption-income elasticities appear across all observable household characteristics: age group, education level, geography, employment status, and economic sector	Table 2, p. 2212	All subgroups show elasticities broadly near or above 1; no systematic pattern concentrating the result in a specific demographic group
R5	The permanent-income (PI) model calibrated for Italy reproduces a flat elasticity pattern close to 1 for all income deciles, matching the data; the result is robust to multiple extensions	Figure 5, p. 2220; Table 3 (calibration), p. 2218	PI model predicts elasticities close to 1 across all deciles; pattern robust to heterogeneous income loadings, negative asset revaluations, and uncertainty shocks (Panels A-D)
R6	The credit-tightening (CT) model predicts a decreasing elasticity pattern across the income distribution (rich smooth, poor adjust more), at odds with the observed flat or increasing pattern	Figure 7, Panel B, p. 2226	CT model predicts rich-household elasticities near 0 and poor-household elasticities well above 1; data show the opposite
R7	Fiscal transfer stimulus is less effective under the PI crisis experiment than under the CT crisis; the MPC from a one-time transfer is positive but decreasing in income in all scenarios	Figure 8, p. 2228	MPC from transfer is highest under the CT crisis (borrowing-constrained households have high MPC), lowest under the PI crisis; PI-crisis MPC close to steady-state transitory-shock MPC

Overall (paper’s conclusion). The consumption-income elasticities observed during these crises are large and broadly uniform across the income distribution, including for households with liquid assets that should be able to smooth under borrowing-constraint theories. The permanent-income view of crises can account for these patterns analytically and quantitatively. Credit-tightening theories face a challenge explaining why income-rich households adjust consumption as much as the average. The difference has policy bite: fiscal transfers are less effective in stimulating consumption when the crisis reflects a permanent income decline than when it stems from a borrowing-constraint tightening.

Theory / model

The model is a heterogeneous-agent small open economy with a continuum of households (pp. 2215-2216). Each household has preferences over an infinite consumption stream (equation 1, p. 2215):

$$E_0 \sum_{t=0}^{\infty} \beta^t u(c_{it}), \tag{1}$$

where $u(\cdot)$ is increasing and concave, $c_{it}$ is household $i$‘s consumption in period $t$, and $\beta \in (0,1)$ is the discount factor. Each period the household receives an endowment $y_{it} = h(\mu_{it}, Y_t)$, where $\mu_{it}$ is idiosyncratic and $Y_t$ is aggregate income with $\int h(\mu_{it}, Y_t)\, di = Y_t$; the baseline sets $y_{it} = \mu_{it} Y_t$. Asset markets are incomplete; households save and borrow only in a riskless bond. The budget constraint and borrowing constraint are (equations 2-3, p. 2215):

$$c_{it} = y_{it} - a_{i,t+1} + (1+r)\, a_{it}, \tag{2}$$ $$a_{i,t+1} \geq -\kappa, \quad \kappa > 0, \tag{3}$$

where $a_{it}$ are bond holdings and $r$ is the international interest rate.

Analytical characterization (Proposition 1, pp. 2216-2217). Under quadratic utility $u(c) = ac - bc^2$ and proportional endowment structure, iterating the Euler equation yields optimal consumption (equation 4, p. 2216):

$$c_{it} = r a_{it} + \frac{r}{1+r} E_t\!\left[\sum_{s=0}^{\infty} \frac{y_{it+s}}{(1+r)^s}\right] - \frac{r}{1+r} E_t\!\left[\sum_{s=0}^{\infty} \frac{\lambda_{it+s}}{(1+r)^s}\right], \tag{4}$$

where $\lambda_{it}$ is the Lagrange multiplier on the borrowing constraint. For a permanent aggregate income shock ($Y_{t+h} = Y_t < Y_{ss}$ for all $h \geq 0$) and small interest rates ($r \to 0$), Proposition 1 states that the consumption-income elasticity is $\varepsilon_{cy} = 1$ for both constrained and permanently unconstrained households: the proportional aggregate shock reduces permanent income of all households proportionally, generating a flat cross-sectional elasticity near 1.

Credit-tightening extension (Proposition 2, pp. 2224-2225). The CT crisis uses a borrowing constraint that depends on aggregate income (equation 6, p. 2224):

$$a_{i,t+1} \geq -\kappa\, f(Y_t), \tag{6}$$

where $f(Y_t) \geq 0$ is non-decreasing; calibrated as $f(Y_t) = Y_t^{\nu}$ with $\nu = 2.7$. Under a mean-reverting transitory income shock plus constraint tightening, Proposition 2 shows that permanently unconstrained households have $\varepsilon_{cy} < 1$ (close to 0 for a highly transitory shock) while constrained households have $\varepsilon_{cy} = g(\varepsilon_{fY}) > 1$. Since income-rich households are more likely to be permanently unconstrained, the CT view generates a decreasing elasticity pattern across the income distribution: rich households smooth, poor households adjust.

Emerging-market extension with nonhomotheticities (p. 2222). To account for the increasing elasticity pattern in emerging markets, where many households are close to subsistence consumption, the model adopts Stone-Geary preferences:

$$u(c_{it}) = \frac{(c_{it} - \underline{c})^{1-\gamma}}{1 - \gamma},$$

where $\underline{c}$ is the subsistence consumption level. Low-income households near $\underline{c}$ have a strong desire to smooth and therefore a lower consumption-income elasticity, generating the increasing pattern with income observed in Mexico and Peru.

Method

The quantitative model uses CRRA utility $u(c) = c^{1-\gamma}/(1-\gamma)$ with $\gamma = 2$ and an AR(1) idiosyncratic income process in logs (p. 2217):

$$\ln\mu_{it} = \rho_\mu \ln\mu_{i,t-1} + \sigma_\mu\, \varepsilon_{it}, \quad \varepsilon_{it} \sim N\!\left(-\frac{\sigma_\mu}{2(1+\rho_\mu)},\, 1\right).$$

The model is solved via value-function-iteration on a discrete state space. Steady-state calibration targets two moments from Italian SHIW data: the liquid wealth-to-income ratio (0.87) and the hand-to-mouth share (0.23) (Table 4, p. 2219), yielding $\beta = 0.90$, $r = 0.02$, $\rho_\mu = 0.88$, $\sigma_\mu = 0.26$, and $\kappa = 0.23$ (Table 3, p. 2218). The model is assessed against untargeted moments including income and wealth distribution statistics (Table 4, p. 2219).

The heterogeneous-loading extension (equation 5, p. 2219) replaces $y_{it} = \mu_{it} Y_t$ with:

$$y_{it} = \mu_{it} Y_t^{\Gamma(\mu_{it})},$$

where $\Gamma(\mu_{it})$ is estimated nonparametrically from the income dynamics of each decile in Italian crisis data.

The empirical measurement methodology follows Blundell, Pistaferri, and Preston (2008): income and consumption are residualized by projecting on household observables (family size, number of children, head’s sex, age, education, and geographic dummies) and time trends before computing group-level averages.

Empirical specifications

Consumption-income elasticity (baseline measurement, p. 2208). For income group $j$, the consumption-income elasticity is:

$$\hat{\varepsilon}^j_{cy} = \frac{\Delta_h \log\bar{c}_{j,\tau+h}}{\Delta_h \log\bar{y}_{j,\tau+h}},$$

where $\bar{c}_{j,t} \equiv \frac{1}{n_{j,t}} \sum_{i \in \mathcal{I}_{j,t}} c_{i,t}$ and $\bar{y}_{j,t} \equiv \frac{1}{n_{j,t}} \sum_{i \in \mathcal{I}_{j,t}} y_{i,t}$ are group-level averages, $\tau$ is the output peak, and $h$ is the peak-to-trough interval. Income $Y$ is monetary after-tax nonfinancial income; consumption $C$ is expenditure on nondurable goods and services; both are deflated by CPI and residualized from household observable characteristics. Confidence intervals use 2,000 bootstrap replications. Synthetic income-group cohorts allow application to countries with only cross-sectional data; results hold for fixed households where panel data exist (Italy, Peru). Episode windows: Italy 2006-2014; Spain 2008-2013; Mexico 1994-1996; Mexico 2006-2010; Peru 2007-2010 (footnote 5, p. 2208).

Business-cycle comparison (p. 2214; Figure 4). For Italy across biennial periods, and analogously for the US using CEX data (1980-2010), the specification is:

$$\Delta \ln c_{q,t} = \alpha_q + \beta_q\, \Delta \ln y_{q,t} + \varepsilon_{q,t},$$

where $c_{q,t}$ and $y_{q,t}$ are average residualized consumption and income in quintile $q$ at year $t$. Estimates of $\beta_q$ are close to 1 for all quintiles in Italy, and range from 0.2 to 0.6 for the United States, consistent with the aggregate evidence that Italy exhibits less consumption smoothing than the US.

Crisis experiments. The model replicates the same elasticity statistic computed from the data. Under the PI experiment: aggregate income follows $\log Y_t = \log Y_{t-1} + \rho_g^t \varepsilon_Y$ with $\varepsilon_Y = -0.15$ and $\rho_g = 0.24$, calibrated to match the aggregate elasticity from Section I. Under the CT experiment: income is transitory (persistence $\rho_Y = 0.9$) and the borrowing constraint tightens via $f(Y_t) = Y_t^{\nu}$ with $\nu = 2.7$; the sensitivity of the constraint to aggregate income is identified by the aggregate consumption-income elasticity (Figure 7, p. 2226).

Datasets used

Dataset	Role in paper	Wiki page
Survey on Household Income and Wealth (SHIW), Banca d’Italia	Italy: household income, consumption, wealth, demographics; main calibration and crisis episode 2006-2014	no page yet
Encuesta de Presupuestos Familiares (EPF), INE Spain	Spain: household income and nondurable consumption cross-section; crisis episode 2008-2013	no page yet
Encuesta Financiera de las Familias (EFF), Banco de Espana	Spain: supplement for household asset holdings and debt data	no page yet
Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH), INEGI Mexico	Mexico: household income and consumption; two episodes (Mexico 1994-1996 and 2006-2010)	no page yet
Encuesta Nacional de Hogares (ENAHO), INEI Peru	Peru: household income and consumption; episode 2007-2010	no page yet
FRED and OECD	Aggregate output and consumption series for macro context and episode identification (Figure 2 sources)	FRED
Consumer Expenditure Survey (CEX), BLS USA	US comparison of consumption-income elasticities, 1980-2010	no page yet

Total sample: 90,199 household-observations across five episodes (Italy 7,067; Spain 21,802; Mexico 1994 13,122; Mexico 2008 27,038; Peru 21,170; Table 1, p. 2209). Data are annual or biennial depending on the survey.

When to read the full paper

Read the original if you are: building or calibrating heterogeneous-agent open-economy models (online Appendix D has full calibration details including aggregate risk, closed-economy variants, and the interest-rate shock extensions); comparing micro distributional evidence across crisis types; assessing credit-tightening models against consumption survey data from Europe and Latin America; or designing fiscal transfer policies for macro crises and want the formal policy-experiment details (Section IIIb and Appendix D4).

Attribution and rights

Source: peer-reviewed, American Economic Review 113(8), August 2023. Copyright 2023 American Economic Association; article freely readable at doi.org/10.1257/aer.20201931 after the AEA 12-month embargo; no Creative Commons licence assigned.

This distillation was extracted by an LLM on 2026-06-25 and is not human-verified or independently reproduced.

Guntin, Rafael, Pablo Ottonello, and Diego J. Perez. “The Micro Anatomy of Macro Consumption Adjustments.” American Economic Review 113, no. 8 (August 2023): 2201-2231. DOI: 10.1257/aer.20201931.