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COPYRIGHT 2000 MIT Press Journals
I. Introduction
OVER THE LAST three decades saving rates have experienced a marked divergence which has been particularly dramatic within the developing world: Saving rates have risen steadily in East Asia, stagnated in Latin America, and fallen in sub-Saharan Africa. These regional saving disparities have been closely matched by diverging growth experiences: Across world regions, higher saving rates tend to be correlated with higher income growth.
This large variation in saving performance across countries and over time raises a number of questions. Why do saving rates differ so much across countries and time periods? How much do public policies contribute to these saving disparities, in comparison to other structural and nonpolicy saving determinants?
From the policy perspective are serious questions about the size--and sometimes even about the sign--of the effects of policy variables on saving rates. How effective is fiscal policy in raising national saving? Does financial liberalization--by raising interest rates, encouraging consumer and housing lending, and raising financial depth--inhibit or encourage private saving? Does foreign lending crowd out national saving? Or perhaps growth-enhancing policies (such as macro stabilization and structural reform) would be more effective in raising saving through higher income and growth than any direct saving incentive?
In this paper we address the above questions empirically by exploiting what we believe is the largest cross-country, time-series, macroeconomic data set on saving and related variables that has been assembled to date. The data set is unique because of various features.(1) First, it encompasses industrial and developing countries and covers nearly thirty years of data. Second, it provides alternative saving measures (for the nation, the central government, the public sector, and the private sector, separately; unadjusted and adjusted for inflation-related capital gains and losses). Third, it has been subject to extensive quality checks, which, among other things, allow us to identify problematic observations and set them aside if necessary.
The objective of the paper is to use this large data set to establish the stylized facts concerning the effects on the private saving rate of its key policy and nonpolicy determinants that are identified in the literature. To do this, the paper estimates a variety of empirical equations for the private saving rate. Private saving regressions are estimated for a worldwide sample of countries, as well as separately for subsamples of industrial and developing countries. For completeness, the paper also presents regression results for the national saving rate. In order to encompass a broad range of saving determinants (and hence theoretical views about saving), we use a variety of reduced-form linear specifications rather than one narrow model of saving derived from first principles.(2) We believe that this approach provides a useful first step to identify the key empirical regularities in need of structural explanation.
We estimate our empirical equations using various panel data procedures, paying particular attention to the issues of simultaneity and country heterogeneity that are mostly ignored in earlier studies. Specifically, our large panel data set allows the use of "internal" instruments to correct for these problems, which permits us to make some progress towards drawing inferences on the effects of policy and nonpolicy variables on private saving rates, rather than merely describing their association.
The paper is organized as follows. Section II summarizes briefly recent cross-country empirical studies of private saving. Section III presents our empirical strategy, describing the data set and estimation approach. Section IV reports the econometric results for the private (and national) saving rate using a variety of samples, regression specifications, and estimation techniques. The paper closes with brief concluding remarks.
II. Determinants of Private Saving Rates in Previous Panel Studies
Table 1 summarizes potential determinants of private saving rates and lists their expected signs according to consumption theory.(3) A number of recent empirical studies have estimated the effect of various economic and demographic variables on private saving rates in cross-country, time-series (panel) samples. To provide a summary on the empirical evidence related to each of the saving determinants under consideration, the last column in table 1 lists the qualitative results of six recent studies using large-panel data samples. They comprise studies for both industrial and developing countries (Masson, Bayoumi, and Samiei (1995); Edwards (1996); Bailliu and Reisen (1998)), for industrial-country samples (Haque, Pesaran, and Sharma (1999)), and for developing-country samples (Corbo and Schmidt-Hebbel (1991); Dayal-Ghulati and Thimann (1997)).
TABLE 1.--DETERMINANTS OF THE PRIVATE SAVING RATIO TO INCOME IN PREVIOUS PANEL STUDIES
Variable Expected Category Specific Variable Sign Income Income level: actual or + Temporary/permanent +/0 or + Terms of trade: actual or + Temporary/permanent +/0 or + Growth rate: actual Ambiguous Rates of return Interest rate Ambiguous Uncertainty Variance of + innovations to saving determinants Inflation or other + measures of macro instability Measures of political + instability Domestic Private credit flows - borrowing Broad money flows - constraints Income - Foreign Foreign lending - borrowing Current account - constraints deficit Financial Private or domestic Ambiguous depth credit stocks Money stocks Ambiguous Fiscal policy Public saving - Public surplus - Public consumption Ambiguous Pension system Pay-as-you-go or - pension transfers to old Mandatory or + fully-funded pension system contributions Fully funded pension Ambiguous assets Demographics Old and/or young-age - population dependency Urbanization Ambiguous Income and Income concentration + wealth Wealth concentration + distribution Capital income share + Variable Empirical Category Specific Variable Findings Income Income level: actual + (1, 2, 3, 4) (5, 6) Temporary/permanent Terms of trade: actual + (2, 4, 6) Temporary/permanent Growth rate: actual + (2, 3) (4, 5, 6) Rates of return Interest rate (1, 3, 5, 6) + (2) Uncertainty Variance of innovations to saving determinants Inflation or other - (4) (1, 2, 3, 6) measures of macro instability Measures of political instability Domestic Private credit flows + (3) borrowing Broad money flows constraints Income Foreign Foreign lending borrowing Current account - (1, 2, 3) constraints deficit Financial Private or domestic - (5) depth credit stocks Money stocks + (1, 3, 4) Fiscal policy Public saving - (1, 3) Public surplus - (2, 5, 6) (4) Public consumption - (2, 6) Pension system Pay-as-you-go - (3, 4, 5) pension transfers to old Mandatory + (4) fully-funded pension system contributions Fully funded pension 0/+ (5) assets Demographics Old and/or young-age - (2, 3, 4) (5, 6) population dependency Urbanization - (3) Income and Income concentration (3) wealth Wealth concentration distribution Capital income share
Note: The qualitative results listed in the last column of this table summarize significant signs of saving regressors in the corresponding tables and columns of the following six studies: 1. Corbo and Schmidt-Hebbel (1991) (table 4); 2. Masson, Bayoumi, and Samiei (1995) (table 2, "restricted model" column); 3. Edwards (1996) (table 2, column 5); 4. Dayal-Ghulati and Thimann (1997) (table 4, column 2); 5. Bailliu and Reisen (1998) (table 1, columns 3 and 4); and 6. Haque, Pesaran, and Sharma (1999) (table 6, columns 4 and 5). Significant coefficient signs are identified by a plus or a minus. Results identified by a zero mean either an insignificant coefficient in the corresponding column of the original study or, when the variable is omitted from the particular specification reported in the column, a significant or insignificant variable in a different column of the same table. Each study is identified in the table by the corresponding number in parentheses.
The common feature of these papers is that they are based on reduced-form saving equations, not necessarily derived from first principles.(4) They differ widely in other dimensions, as they are also based on different sample periods and countries as well as on different model specifications and estimation techniques. Not surprisingly, only a few saving determinants appear to be consistently significant across different studies and with their estimated signs according to theory. They include the terms of trade, domestic and foreign borrowing constraints, fiscal policy variables, and pension system variables. Regarding other determinants for which consumption theories either differ regarding their signs or point toward ambiguous signs (as in the case of income growth and interest rates), these empirical studies differ widely. They differ also in reported significance levels of variables for which theories tend to agree on expected signs, such as income level, inflation, and demographic dependency ratios.
III. Empirical Strategy
The above empirical studies capture a number of factors relevant to saving decisions, but they vary considerably in terms of data coverage and quality, empirical specification, and econometric procedure. Our primary objective here is to extend this literature by providing a comprehensive characterization of the empirical association between private saving rates and a broad range of potentially important saving determinants using the best available data. To do this, we complement and extend previous work along three dimensions. First, we use the largest set of consistent macroeconomic data on saving assembled to date. Second, we adopt a reduced-form approach encompassing a variety of saving determinants identified in the literature, rather than adhering to one particular, narrow, structural model. Third, we employ a variety of estimation methods but focus our attention on estimators that attempt to control for heterogeneity and simultaneity, two problems that likely plaque most previous empirical studies.
A. The Data
Our basic data set draws from the saving database recently constructed at the World Bank and described in detail by Loayza et al. (1998a). To our knowledge, this database represents the largest macroeconomic data set on saving and related variables presently available. It comprises a maximum of 150 countries and spans the years 1965 to 1994. The data have been subject to extensive consistency checks; hence, they also represent an important improvement in terms of quality relative to other existing data sets.(5)
The data set excludes the countries for which we found inconsistencies in basic National Account, fiscal, and financial data. These data limitations prevented the construction of reliable saving measures, their disaggregation into public and private saving, and/or the calculation of the inflation adjustments for the latter. For some of the key variables in this paper, the effective data coverage in countries and years is therefore limited. Nevertheless, for the "core" private saving regression, presented below, we initially count with 1,254 complete observations spanning the years 1966-1995.
From this initial sample, we decided to exclude the observations corresponding to episodes of high inflation. We base this decision on the fact that high inflation distorts severely measured public and private saving (particularly the inflation-adjusted saving measures).(6) Moreover, in general high inflation renders National Account statistics largely unreliable. For practical purposes, we set a threshold of [+ or -] 50% annual inflation. We apply the same threshold to the real interest rate, which in cases of high inflation is mostly driven by inflation. For the core specification, these data adjustments lead to the direct loss of 49 observations.(7)
In order to achieve a minimum time-series dimension, as well as to reserve sufficient observations to implement our instrumental-variable estimators described below, we limit our sample coverage to those countries with at least five consecutive annual observations. After all these adjustments, the sample for our core specification consists of 1,148 observations. Because four observations per country must be set aside for the construction of instruments, the core regression sample consists of 872 observations for 69 countries (20 industrial and 49 developing). As explained below, we also estimate regressions for the national saving rate and for private saving rates derived from a narrower definition of the public sector. For these regressions, the available sample comprises approximately 1,800 annual observations for 98 countries in the case of national saving rates and between 750 and 900 observations for 69 countries in the case of private saving rates, depending on the precise definition of the private and public sectors.(8) This sample coverage exceeds that of Edwards (1996)--who considers 32 countries--and Masson, Bayoumi, and Samiei (1995)--whose sample includes 61 countries.
Finally, note that these panel data sets are heavily balanced, with the number of time-series observations varying considerably across countries. The top panel of table 1 provides information as to the composition of the core regression sample per decade and development stage. Developing countries account for over half of the total number of observations, and the 1980s is the decade most heavily represented in the data.
The precise definition of saving that we use also deserves comment. As in Loayza et al. (1998b), for the nation as a whole our basic income measure is gross national disposable income (GNDI), equal to GNP plus all net unrequited transfers from abroad.(9) Gross national saving is then defined as GNDI minus consumption expenditure, with both measured at current prices.
In turn, for the private sector we implement four alternative measures of disposable income and gross saving. These follow from the definition chosen for the public sector (that is, consolidated central government or broad public sector) and from whether the private and public income and saving figures are adjusted or not for capital gains and losses due to inflation. We respectively label the four alternatives that result as
* CU (unadjusted data corresponding to the central government definition),
* CA (same as CU but after adjusting for inflationary capital gains and losses),
* PU (unadjusted data corresponding to the public sector definition of the government), and
* PA (inflation-adjusted PU data).
Notice that by construction the CA and CU configurations lump local governments and public enterprises together with the private sector. In turn, the PA and PU definitions of the public sector correspond to either the general government or, when available, the consolidated nonfinancial public sector, inclusive of public enterprises. Hence, of these four alternatives, the analytically preferable one is clearly PA. This is the private saving definition on which we base our core regression and most of our experiments. In contrast, most empirical studies use the CU measure, which is more readily available but analytically problematic.
In each case, gross private saving is computed as the difference between gross national saving and...
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