APPENDIX: Data Sources and Empirical Estimates
The concept of savings used in this study is that of gross national savings (GNS).24 Figures for estimated GNS were obtained by adding the current account balance to gross domestic investment (GDI). The current account data were taken from the balance of payments account, whereas GDI figures were taken from national accounts. Note that the savings figures include net current transfers, exclude statistical discrepancies, and use two different data accounts (national accounts and balance of payments). Net current transfers have been included to make the savings figures representative of available resources for investment purposes. Statistical discrepancies have been excluded on the presumption that consumption figures are perhaps less reliable than other national accounts categories and may be underestimated. Exclusion of the statistical discrepancies produces underestimates of savings, which are not as damaging as overestimates in a discussion of high savings rates in Asia. Data from balance of payments accounts are not always consistent with data from national accounts; this was the case with two countries in our study—India and Indonesia (see Sigit (1985)). The uniform practice of taking the figures of foreign savings for all the eight countries as the current account balance (with sign reversed) was followed. The average official exchange rate for every year was used to convert foreign currency figures into local currency.
The population figures were mid-year estimates. The price index used to deflate figures at current prices to obtain their constant price counterparts was the implicit GDP deflator. For some data-deficient countries (for example, Indonesia), the consumer price index was used to extrapolate the available data on the implicit GDP deflator.
All the data used in the study were taken from the International Monetary Fund’s International Financial Statistics (IFS), with three major exceptions. Data on age composition were from the World Bank’s demographic data base; the data on personal disposable income for India were from the Government of India’s National Accounts Statistics (Central Statistical Organization, January 1987); and the data on consolidated government revenue and expenditure were from the Fund’s Government Finance Statistics Yearbook. “Government” refers to the consolidated government sector, comprising central, state, and local governments.
The inflation variable is the rate of rise in the consumer price index. The terms of trade is the unit value index of exports as a percentage of the unit value index of imports. Exports as a percentage of GNP were calculated by taking the relevant figures from the national accounts data in IFS. Money supply figures used in the analysis refer to narrow money. The data for GNP in the United States are at constant prices.
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Mr. Lahiri, an economist in the European Department of the Fund, is a graduate of Calcutta University and the Delhi School of Economics, University of Delhi. This paper was written while he was visiting the Asian Department, on leave From the Delhi School of Economics. He thanks Kajal Lahiri and colleagues in the Fund for helpful comments.
In more recent times, Graham (1987, p. 1509) found that these two factors explain almost two thirds of the variations observed in the savings rates of major industrial economies during the 1970s.
Ravallion and Sen (1986) have shown the questionable nature of the assumption of uniform response of savings across countries.
Serious doubts have been raised about the validity of Ricardian equivalence. For a demonstration of its invalidity in developing countries, see Haque and Montiel (1987).
Most existing studies use gross national product (GNP) as the explanatory variable in the analysis of savings behavior. Here, however, private disposable income is estimated and used in the empirical investigations, since it is the appropriate concept of income in the context of private savings.
Branson and Klevorick (1969). however, found evidence of a negative effect of inflation on savings in the United States. Similarly. Howard (1978) found that, although inflation led to increased savings in Canada, the United Kingdom, and the United States, expected inflation discouraged savings in Japan.
Inflation leads to substitution of nominal assets by real assets, including consumer durables. Because what is measured in developing countries is consumption expenditure and not consumption, measured consumption will rise and measured savings will be adversely affected.
For Indonesia, the period covered is 1967-85—that is, the period after hyperinflation.
Social security institutions, such as the Employee Provident Fund in India. Malaysia, and Sri Lanka or the Central Provident Fund in Singapore, have played a crucial role in mobilizing contractual forced savings in Asian countries. There are reasons to believe that such compulsory savings were not neutralized by voluntary dissavings; see, for example, Datta and Shome (1981). The importance of these schemes could not be examined here because of the lack of readily available data.
Note the unfortunate change in the use of the symbols c and y. Although they have been used in the earlier subsection to denote consumption of a representative agent and his or her youth, in what follows they are used to denote the natural logarithms of per capita private consumption and income. This is mostly in deference to convention.
Use of the implicit GDP deflator for deriving real private consumption, on the one hand, and use of the consumer price index to obtain the rate of inflation, on the other, needs a word of explanation. It is preferable to deflate nominal income and consumption, two variables that appear on two sides of the consumption function, by the same price index. The implicit GDP deflator being the natural choice for the income variable, this same index has been used rather than the consumer price index for deflating consumer expenditure. In the case of the inflation variable, the preference runs in the opposite direction because of the more important role that durable goods play in the determination of the consumer price index relative to that in the GDP deflator.
Note that the neglect of governmental property income, interest subsidies, retained earnings of the corporate sector, and depreciation may have introduced a bias in the income series.
Note that, because of the presence of a dynamic lag structure in the model, consumption reacts to current as well as past incomes. Thus, strictly speaking, there should be a dummy variable to take account of the imprecision in the past income figures even in years when the contemporaneous income is measured correctly but the relevant past incomes are not. This procedure, however, would lead to the introduction of more than one dummy variable, to nonlinear parametric restrictions, and to considerable complications.
The hypothesis that
As reported later, for Sri Lanka the hypothesis
The present model departs from Davidson and others (1978) because of the presence of variables other than only income and consumption. Some bold uniformity assumptions about the dynamic response of consumption to changes in inflation, the terms of trade, and export orientation have been made because of the limited number of observations.
Appropriate F-tests were carried out before dropping one or more variables from the equation for any country.
See Pagan (1984) for the complication arising from generated regressors. Exports as a proportion of GNP (x) are present as an explanatory variable in equation (6) but not in equation (9). This renders the calculation of the correct standard errors particularly complex.
For the Philippines, the short-run increase in the APS appears to be too large relative to other countries. This, along with the rejection of and the insignificance of demographic variables, shows the poor performance of the model for the Philippines.
The insignificance of the age-dependency variable in the Philippines’ consumption function could be due in part to the high spurious correlation (-0.92) between the age-composition variable and the dummy for data discontinuity.
Much as for the Philippines, the performance of the model is relatively poor for Thailand because of the perversity of the coefficient for the demographic variable and rejection of H3
Ram (1982) and Rossi (1989) found that dependency rates are not important for savings rates in developing countries. Our results are sharply different. Their studies differ from the present one in three respects: the country coverage, their use of a static framework without any dynamic lag structure, and the functional form. Ram and Rossi’s results are obtained from a very large cross section of time-series data. Although the results reported in the present study relate to individual time-series analysis, an unambiguously positive impact of low dependency rates on private savings was found, even in a pooled analysis of the eight countries.
Admittedly, this study has not investigated whether the composition of dependents in terms of children and elderly people has any impact on savings over and above that of the total proportion of dependents in the population. This question merits further attention.
The high APS in India in the long run may seem surprising. It must be recalled, however, that India has had a relatively low growth rate and little change in the age composition of the population, vet its savings rate has been high.
The difference between GNS and gross domestic savings (GDS) is net factor income from abroad and net current transfers. Because the main interest was to understand the amount of resources available for investment, the analysis concentrated on GNS rather than GDS.