The LCH is derived from the aggregation of finite-lived overlapping generations and introduces age-related consumer heterogeneity. Consumption in any period is a function of both wealth and disposable income, where the marginal propensities to consume from either are dependent on factors such as age, life expectancy, and working years. The LCH posits that individuals will dissave when thay are young, have positive saving during their working years, and run down their savings in retirement. Hence, saving follows a hump-shaped pattern for each consumer.
Variables associated with the LCH have, most often, found strong empirical support in the cross-country macroeconomic data. Most often, studies that estimate reduced form saving equations using panel or cross-sectional data find that the age dependency ratio is significantly and negatively linked to saving. While the values of the estimated coefficients are sensitive to the set of regressors used, the sample countries, and how the dependency ratio was measured, the results appears to be robust across a broad array of specifications and data sets.39 As the LCH would predict, the higher the share of the very young and the very old (who dissave) in the population--the lower the saving rate. As shown in Table I.14, two of the studies that examined
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Other demographic variables frequently included in the regression analysis are population growth rates and average retirement ages.
this issue empirically (Colombia and Peru) do, indeed, present similar evidence.
Unlike the issue of liquidity constraints, where the results from the study of the micro and macro data converged, the evidence on the LCH is less conclusive. As noted, there is some support for the LCH at the macro level. In the case of Peru, the pattern of household saving across age groups in cross-sectional micro data appeared to be broadly consistent with the hump- shaped pattern predicted by LCH. Yet, two of the studies that analyzed micro household data find little support for LCH predictions. In the case of Mexico, the number of children aged 12 or less per households has a positive and significant coefficient in the saving equations, while households headed by someone aged 65 or more (the oldest group) saved more, although its statistical significance depended on the year examined. In a similar vein, Japelli and Pagano (1998) have little success in explaining Italy’s declining saving rate on the basis of the life cycle model’s predictions. During a period of slowing economic growth, the LCH would predict that saving would fall, as the incomes of the highest saving age group--those middle-aged and actively employed--would be proportionately hit the hardest. Hence, a priori one should expect to find in the micro data that the decline in saving rates is largely confined to this working age cohort. The data presented in Japelli and Pagano (1998 this volume) instead reveal declines in the saving rates of all age groups. Perhaps, the lack of conclusive evidence on the causality from growth to saving in these studies reflects an ambiguity in its underpinnings in the LCH.
I.3.7. Other determinants of saving
In this subsection, we focus on two additional variables that in both theory and existing evidence emerge as potential determinants of private saving. The first variable, income
distribution, has usually been coupled with household saving, while the terms-of-trade may both affect the household and the firm.
Income distribution
The bulk of the theoretical literature on household saving has suggested that, other things equal, a more skewed income distribution would produce a higher level of aggregate saving. The argument rests on differential propensities to consume out of current income, with the rich consuming a proportionally lower share of their income. However, a recent strand of the political economy literature has suggested that there is a positive link between political
instability and income inequality.40 The argument runs as follows: Political instability increases uncertainty; uncertainty adversely affects investment, and; lower investment means lower growth. Taking this causal chain a step further, if, indeed, growth causes saving as Carol and Weil (1993) suggest, then countries with more income inequality and lower growth would also be expected to have lower saving rates. Hence, on theoretical grounds, the sign of the coefficient on income inequality is ambiguous. Previous, empirical studies (see Plies and Reinhart, 1998, for a recent survey) have found scattered evidence in favor of both positive and negative links. A recent study by Schmidt-Hebbel and Servén (1996), using a comprehensive panel cross- country data set on income distribution, found no significant link. This lack of significance was both robust to the specification of saving used as well as to the choice of sample countries. Table I.15 summarizes the results of the studies in this volume that examined this issue. The studies for Spain and Venezuela in this volume examined this issue using macro data; in neither case was the proxy for income distribution significant.
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On the basis of the household data, the Mexican study offers some provocative results. While the issue of income distribution is not explicitly addressed, Calderón-Madrid (1998 this volume) links household saving to educational attainment, specifically, years of education. Presumably education and income levels are positively related, indeed the household survey data from Peru illustrates this positive correlation. Yet, Calderón-Madrid finds that more educated households save less. The interpretation given in that paper is that these households have access to credit, while less educated households heads do not.
The terms of trade
As with income distribution, the predicted theoretical sign of the relationship between the terms of trade and saving is ambiguous. When a country experiences an adverse temporary
terms of trade shock, (a decline in the relative price of its exports), this temporary decline in current income should lead to dissaving, based on consumption smoothing considerations--this is the basis of the Harberger-Laursen-Metzler (HLM) effect and it follows from the permanent income hypothesis (PIH). The PIH suggests that there is a difference between the short-run and long-run marginal propensity to consume, where the difference depends on the perceived permanence of the change in income. If the decline in income is seen as permanent, abstracting from habit persistence, consumption would be reduced accordingly; if the shock is temporary, consumption does not adjust and saving declines.
However, this is only part of story. Following the shock, imports are now expensive relative to other goods in the basket. This relative price shift can be expected to lead individuals to substitute away from the imported good and consume less of it--this is known as the
relationship between the terms of trade and saving and consumption-tilting a negative one. Presumably, the issue can be settled empirically. Of the four case studies in the
following chapters that examine this issue, all find a positive and influence of the terms of trade on saving, consistent with the HLM hypothesis. In two cases, El Salvador and Peru, the terms of trade are part of the cointegrating vector, suggesting these influence the long run level of saving, if not necessarily its short-run dynamics. In the case of Venezuela, estimates of an Euler
equation derived from a model that allows for consumption of traded and nontraded goods, as in Ostry and Reinhart (1992), are used to simulate the effects on saving from a terms of trade shock; these exercises suggest saving in Venezuela is highly sensitive to the terms-of-trade. Lastly, while for the case of Argentina, the correlation between saving and the terms of trade is positive, it is close to zero and not likely to be statistically significant.
Perhaps, it is not surprising to find that of the four case studies that examined the saving/terms-of-trade link, the three that find a strong systematic and positive relationship are the three countries that have the least diversified export structure and their export revenues are heavily dependent on one or a handful of primary commodities. In the case of El Salvador, it is coffee, in Peru minerals and ores, and in Venezuela oil.