CHAPTER 1
INTRODUCTION
1.1: An Overview
In the early 1950s, theory was developed by Franco Modigliani and his student Richard, Based on the assumptions of how people want to spend their income over the life-cycle with limited resource available to them. By building up and selling of assets, workers can make arrangements for their retirement; adapt their consumption to their needs at different ages, regardless of their income at each age. This theory leads us to results which are very important, but not obvious in the economy, that the national savings does not depend on the level of National income, but its growth. With time this theory received a massive support and encouragement due to its importance and Modigliani was awarded Noble prize in 1985 by Royal Swedish Academy.
The rationality of the life cycle hypothesis with the theory of consumer choice has not received only guarantee of its internal coherence, but also comes with a generality that reflects much of its durability. The core theory of life cycle explain the instincts of consumption and savings, but it is extracted from fundamental principles underlying that could be used to extend the model to address a wide range of issues on consumption and savings, many of whom had not been thought in 1950. Social security is a key policy issue today, and although it plays a little in the original formulation, the framework can be easily extended to help us reflect on the consequences of alternative policies. Economic theory and methods change over time, and cycle theory of life has been enriched and broadened so that was not possible in the 1950s. The assumptions that were originally required for traceability have been relaxed. For example, Modigliani and Brumberg original formulation has recognized that planning life cycle requires people to look toward an unseen future and is difficult to formulate theoretically satisfactory and tractable models of how people behave in the face of uncertainty. In the subsequent half-century, economists and others have developed methods to cope with uncertainty, and the economy has absorbed the tools of statistical analysis of time series that allows us to process expectations for the future in a more coherent, and much work in recent was devoted to the theory of life cycle rework to incorporate rigor uncertain the future. The tools are not available to undertake such a task in 1950.
This prediction, which in the 1950s were untestable received empirical Modigliani and subsequent work by other researchers help. Without it, we have very little about as many important issues, like Private and public provision of social security, the economy's impact on the stock market, National savings impact of population change, the role of savings in economic development, and National wealth determinants. It is used to examine savings and retirement spam of a person. The consumption of young people often exceed their income, this is because they need housing, education and often are low on income or are dependent on their parents. In middle age, earning rise and through that the debt is paid off, saving raises to keep the consumption smooth for retirement. Finally, in old age saving starts to vanish and consumption rises. In the Early stages of theory only cash form of savings were in consideration which limited the practical impact of theory on economy. Later with the help of more research results other form of assets were also assumed as saving in Life cycle hypothesis. Many people today save in the form of assets, that could be due to two main reasons, first that they may gain benefit from that asset and later in life they can sell it off to smooth their consumption in retirement, second to gain income or profits on assets and again sell them of later in life if needed, Assets like house, car(durable goods) and securities.
The graph shows that gross saving is increasing over the years because Population ages 15-16 is increasing at a higher growth rate and is much higher in values in relation to other ages in all years. According to life cycle hypothesis the reason is that population of 15-64 is a working young population before retirement and they tend to save more than any other age group. So the overall saving is rising.
The story of the life cycle is one in which the wealth of the nation was passing around; Young have little wealth, middle-aged group have more wealth and peak in graph occurs just before retirement. As they live through, retirees sell their assets to provide food, housing, entertainment and retirement. Consider an economy in which the population is growing, or in which incomes are increasing so that each generation is better their Ancestors. With population growth, there are more young people in the economy which means they will be saving more and old age group will be less then young in number which will result in more saving in the economy than dissaving, There will be positive net savings. If incomes are rising, young to save money on a larger scale than the old ones are dissaving so that economic growth as the population growth, causes of positive economics, and more growth, the higher the savings rate. Infact, it No matter if it's the population growth or growth of income per capita, which economic issues is simply the growth rate of total income. The income level itself does country material, and poor save the same share of their income than rich countries. In an economy without growth, wealth will simply be passed around, no new wealth is created. Total wealth in the economy depends on the length of an individual's retirement, and in simple cases, the report of a wealth of the country's income is half the average length of retirement, a prediction remarkable for its precision, simplicity, and the absence of unspecified parameters. More generally, the wealth ratio on income is less than the fastest rate of growth of the economy, and is on her greater when the growth rate is zero.
1.2: Importance of the study with respect to the world
The theory of Modigliani life cycle is a nice piece of theory, supported by many years of experiential studies work by both supporters and detractors. But there is more than that. It is the theory of the life cycle contributes to we think a lot of important political issues on which we would otherwise have very little to say. Through life cycle hypothesis we should be able to answer appropriately to, How do Government's disposal to interact with private provision? Is it a state pension as a substitute for private retirement savings and, if so, how? How changes in retirement behavior affect the economy? The social security systems affect the age at which people retire and how much amount of wealth in the economy? How does a booming stock market affect the cost of people and savings? More broadly, all those who believe economic development must consider the role of savings in economic growth. Is saving the source of growth, or simply it's accordingly? What about demographics? The aging of China reduce its savings rate and bring growth to stop? Is that what happened in Japan? Is this the wealth of the nation simply a retirement vehicle? And what about the Rothschilds, the Rockefellers and the
Queen of England, not to mention Bill Gates? Is it true that they do not play an important role in the accumulation of national wealth?
1.3: Importance of study with respect to Pakistan
Life cycle hypothesis has great importance for Pakistan, in the era of 2003-2007 Pakistan faced very high inflation with respect to previous years, which resulted in both pros and corns for the economy. If Pakistan has used Life cycle hypothesis it would have handled money supply more efficiently, life cycle hypotheses helps and supports decisions in relation to monetary policy, the saving and consumption rate of an economy and money supply requirements. Today due to massive amount of terrorist attacks Pakistan stock market is being boomed frequently, through life cycle hypothesis we can make the results of crashing stock markets with people saving patterns. The relationship of social securities with different age groups and fungilbilty of assets effecting different forms of asset saving and money blockage in an economy.
Figure 1, shows saving starts when an individual starts earning at young age, income and saving is assumed to be constant till retirement, whereas consumption is assumed to be constant through life till death. Dissaving starts after retirement when an individual stops earning and sharp decline is shown in wealth after retirement.
1.4: Research Question
"Do the people of Pakistan follow a saving and consumption pattern compatible with Modigliani's life cycle hypothesis, also is age a negative determinant of wealth and To what extent do demographic characteristics such as age, gender, and race affect savings"
CHAPTER 2
LITERATURE REVIEW
2.1: housing and non-housing goods
Yang (2006) conducted a basic research with the aim of development or construction of the theory aiming at extension of the theoretical knowledge of life cycle hypothesis. He compared and studied housing and non-housing goods with the modification to simple life cycle hypothesis which can more resemble the consumption patterns. He stated that an individual occupies house due two main reasons: it can be used as a utility and also can be used as collateral. The modified framework he came up with had some frictions in it which were to be faced by the households: income risks; borrowing constrains; absence of an annuity market to cover against an indefinite lifetime; and operation costs of trading houses. He claims that household save to self-insure and to enjoy services from housing. He gathered consumption data and asset data to construct synthetic cohorts from each data set. In the model he has taken some main dependent variables Technology and timing; The rental market; Demographics; Consumer's maximization problem; Transaction costs; and Borrowing constraints. The Numerical results studies the implications of the classic economy for homeownership rates by age and for the life-cycle consumption and wealth outlines for both homeowners and renters.
2.2: Government debt and social security in a life-cycle economy
Fujiwara (2007) conducted a research to construct a dynamic new Keynesian model that joins life-cycle behavior. Government debt and social security in a life-cycle economy. They also studied whether considerations of life-cycle and demographic structure change the active properties of the monetary business cycle model, specifically the degree of extension in urge responses. Bean (2004) summarizes the previous findings in this field, pointing out their implications for a central bank:
1) Demographic expansions represent a macroeconomic tremor, which may lead to sudden movements in asset prices and shrill movements in saving activities.
2) The natural rate of interest drops both along the switch path and in the steady state.
3) The natural rate of unemployment may also be affected through the matching mechanism5.
4) The wealth network is likely to become a more central spread channel of monetary policy than intertemporal substitution.
5) The Phillips curve is blarney due to immigration and the enlarged input of retired workers whose amount of labor is considered to be comparatively elastic.
6) The electorate for keeping inflation low will be larger appreciations to higher average wealth accumulation.
7) Societal aging may persuade diversification and risk-fluctuating with a securitized market rather than bank-intermediated finance, which has inferences for financial stability.
The model they used is canonical model, with the main variables of Firms, Capital producers, Financial intermediaries, households and monetary policies. The sub variables and intervening variables are also discussed in detail. Paper concluded that First, the natural rate of interest differs as demographics change. Second, the structural jolts to the economy have distorted effects on heterogeneous agents, which are workers and retirees.
Bullard (2007) conducted a research on general equilibrium life-cycle economy with which capital of households consist both consumption and leisure in their time for utility function. They documented that household age-consumption profiles, adjusted for both economic growth and family size, have a distinct and statistically significant hump, with actual consumption on the increase during ages 20-40 and falling off during ages 50-70. Paper has also done a quantitative analysis on US data of households. They concluded that taking account of the effects of consumption leisure substitutability in household preferences may help explain the life cycle consumption data that has been viewed as puzzling.
2.3: Different types of financial assets
Levin (1998) conducted a research on life-cycle model that it can explain how the consumption of individuals at or near retirement vary with changes in different types of financial assets. The behavioral life-cycle model as developed by Shefrin and Thaler is a simple model of self-control based on three ideas. First, individuals are tempted to spend all their resources on current consumption instead of saving for the future. Second, individuals who save, overcome this self-control problem by investing in a variety of assets that have different levels of temptation associated with them. Third, setting up these mental accounts implies that individuals engage in `framing' a person's consumption spending not only depends on total wealth but also depends on how that wealth is allocated among assets with differing levels of `temptation'. For example, individuals are more willing to spend assets they have labeled current income than those they have labeled wealth or those that they expect in the future. This paper has four major results. First, spending seems to be very sensitive to changes in income but much less sensitive to changes in wealth. Second, close examination of the relation of wealth to consumption reveals a pattern in which individuals treat assets as not being fungible (equivalent to each other). Third, liquidity constraints affect consumption not as the conventional model predicts but in a manner consistent with the existence of either financial or psychological transaction costs. The affect of these constraints may also be evidence of a behavioral bequest motive. Finally, the amount spent on particular goods seems to depend not only on the individual's total resources but also on how those resources are split between different assets.
Gary D. Hansen (2008) conducted a research on the quantitative implications of ambiguity about the length of life and a absence of annuity markets for life cycle consumption in a general equilibrium intersecting generations model in which markets are else complete. The paper concluded that the empirical life cycle consumption profile in the US has a hump that peaks around age 50. This is typically considered a puzzle since the complete markets life cycle model would produce a consumption profile that is monotonic over the life cycle.
Barucci (1995) conducted a research on optimal saving problem over a finite horizon for a 'hedonistic' consumer having increasing marginal utility. The results obtained in this paper and they show that there is a discontinuity between the characterization of the finite horizon optimal solution and of the infinite horizon optimal one.
2.4: Overconfidence in life-cycle consumption/saving model
Caliendo and Huang (2007) conducted a research on the inferences of consumer overconfidence in life-cycle consumption/saving model. Our main analytical result is a necessary and sufficient condition under which any degree of overconfidence about the mean return on savings can yield a hump in the work-life consumption. There character is that consumer overconfidence may not only have important insinuations for trading and asset prices, but for consumption as well. We thus study the implications of consumer overconfidence in the general life-cycle consumption/saving model. The paper has have shown that overconfidence concerning the mean return on savings can produce a work-life consumption hump while overconfidence about the variance of the return on the long-run average it has little effect on the behavior of consumption (life-cycle), and that fairly strong with various genuine modifications to the baseline model is our basic conclusion.
Graham (2000) conducted a research to find the evidence from survey on faculty pay-cycle variable disputes with the neoclassical theory of consumer behavior. It is more promising to the behavioral life-cycle theory of Shefrin and Thaler (1988).
2.5: Impact of Inflation
Mueller (1959) conducted a research on consumer reaction to inflation. The paper has studied the patterns of individuals saving and consumption in relation inflation. Paper concluded that in the past there have been times when consumers with differing price expectations did not differ in their rate of discretionary spending; while there have been other times when perceptions of price advances led to a reduction in the rate of consumer spending.
Japelli (May 2005) reviews some of the most important results of the life cycle hypothesis for understanding individual and the behavior of aggregate savings. He then turns to the implications for fiscal policy and social security,
highlighting the seminal contribution of Modigliani. Over time competing theories have emerged, and some empirical results are difficult to reconcile with LCH. The article puts light on the relationship of fiscal policy with fiscal polices. Researched tries to show the two way effect that how fiscal policies effect national savings and how national puts effect on making of fiscal policy. The importance of this relationship is very vital, without knowing the consumption and saving rate in an economy good fiscal policy can never be implemented. Article also puts focus on social securities and the age-profile of saving and wealth, that how social securities changes with the changes of age-profile.
CHAPTER 3
METHODOLOGY
3.1: Research type
It is a quantitative research. Data needed for research is of income propensities and saving patterns, which is available from previous government surveys. As Modigliani was a classical researcher, means there is no room for probability in this research, so qualitative research will be of no use.
3.2: Data type and research period
Secondary data will be used in this research. Data of Government surveys about income, saving and its variables will be used. Data will differentiate by age group, gender and growth. Data is time series, for 20 years, from year 1988 to year 2008.
3.3: Sources of data
World Bank Website
Most of the data related to my variables was in percentage of total, so I calculated and converted percentages into figures by multiplying it with the total value. References to my variables under construction are in reference chapter.
3.4: Theoretical framework and variables under considerationC:\Users\abdullah\Desktop\Theoratical fm new.png
3.5: Key Definitions
Life Cycle Hypothesis: The Study of people saving and consumption behavior in respect to their ages (young, middle-age and old) constant percentage of the life income's present value.
Consumption pattern: The combination of qualities, quantities, acts and tendencies characterizing a community or human group's use of resources for survival, comfort and enjoyment. (Source: ODE / RHW).
Stationary Population: A stable population in which the rate of natural increase is zero and there is constant size and unchanging age distribution.
Fujiwara, Y. Teranishi, 2008. Journal of Economic Dynamics & Control.
Gatler, 1997. National Bureau of Economics Research.
Monetary Policy: The use of the money supply and/or the interest rate to influence the level of macroeconomic activity and other policy objectives including the balance of payments or the exchange rate.
Fujiwara, Y. Teranishi, 2008. Journal of Economic Dynamics & Control.
Types of Assets: Anything tangible or intangible that is capable of being owned or controlled to produce value and that is held to have positive economic value is considered an asset.
Levin, 1998. Economic Behavior & Org. 59-83.
Annuities: income from capital investment paid in a series of regular payments.
Natural Rate of Interest: the real funds rate predictable over the next year or two
Demographics: Key attributes - such as gender, income level and age - that make up a group of people.
Life Expectancy: an expected time to live as calculated on the basis of statistical probabilities.
Workers: actively engaged in paid work; "the working population".
Retiree: someone who has retired from active working, where a person stops employment completely.
Age: Age group of 0-14, 15-64 and 65 above.
Gender: Male and Female.
3.6: Population, Working population and planned sample
Total population will be of indicators available from survey of World Bank, Pakistan. Working population will be between the Age of 15-64. Planned sample is of total population of Pakistan.
3.7: Research hypothesis
As my research has two dependent variables, so I have constructed different hypothesis testing for each variable (Saving and Consumption).
3.7.1 Hypothesis Testing for Savings
Ho: Monetary Policy insignificantly affects the saving of an individual.
H1: Monetary Policy significantly affects the savings of an individual.
Ho: Savings of individuals at or near retirement do not vary with changes in different types of financial assets.
H1: Savings of individuals at or near retirement vary with changes in different types of financial assets.
Ho: Age group 15-65 has insignificant positive effect on the saving
H1: Age group 15-65 has significant positive effect on the saving
3.7.2: Hypothesis Testing for Consumption
Ho: Monetary Policy insignificantly affects the consumption of an individual.
H1: Monetary Policy significantly affects the consumption of an individual.
Ho: Income Tax insignificantly affects the consumption of an individual.
H1: Income Tax significantly affects the consumption of an individual.
Ho: Life expectancy has insignificant effect on the consumption
H1: Life expectancy has significant affect on the consumption
3.8: Techniques
To analyze the relationship between different variables I have used the statistical technique. Due to several variables, multiple regression technique will be used; as a result it will show the strength of different independent variables with dependent variable. I will be running two separate regressions as my research consist of two dependent variables.
3.9: Data analysis
My data is secondary and Time series so i will be using Eviews to run regression analysis. It will show the strength of relationship between independent variables and dependent variable. Eviews is software used for regression analysis.
3.10: Data interpretation
After running a regression analysis on Eviews data is analyzed and the results are concluded.
CHAPTER 4
RESULTS AND ANALYSIS
4.1: Results
I have tested two regressions as in my model there are two dependent variables, Saving and Consumption.
4.1.1: Consumption Results
Parameter
Estimate
Standard Error
T Statistic
P-Value
CONSTANT
-3.19752
1.67424
-1.90983
0.0885
Labor force
-885.148
2845.22
0.3111
0.7628
Population ages 0-14
3581.17
1342.58
2.66737
0.0257
Money supply
0.00460
0.014476
0.318189
0.0576
Population ages 15-64
-12982.4
6974.89
-1.86131
0.0956
Population ages 65 above
23708.6
13125.5
1.8063
0.1043
Quasi money
-0.00273
0.018500
-0.14799
0.0856
Taxes on income
-0.11790
0.07016
-1.68051
0.1272
Life expectancy
3.01826E10
1.05183E10
2.86953
0.0185
Source
Sum of Squares
Df
Mean Square
F-Ratio
P-Value
Model
7.68862E21
7
1.09837E21
173.95
0.0000
Residual
5.68287E19
9
6.3143E18
Total (Corr.)
7.74545E21
16
R-squared = 99.2663 percent
R-squared (adjusted for d.f.) = 98.6956 percent
Standard Error of Est. = 2.51283E9
Mean absolute error = 1.43175E9
Durbin-Watson statistic = 2.04385
Household consumption = -3.19752E11 - 885.148*Labor force +
3581.17*Population ages 0 to 14 + 0.00460615*Money supply -
12982.4*Population ages 15 to 64 + 23708.6*Population ages 65 and above - 0.00273807*Quasi money - 0.117906*Taxes on income
4.1.1.1: Analysis
Equation shows that Labor force has negative relationship with Household consumption, Population of age 0-14 has a positive relationship which shows that this age group consume more. Population of age 15-64 has negative relationship because savings are high and consumption in low in this age group. Population 65 above has a positive relationship because consumption is high in this age group as saving will fall. Quasi money and Taxes has negative relation.
The variable shows a statistically significant relationship at a 99% confidence level. The ANOVA table depicts a P value less than 0.01 that supports my stance.
R square is 99.2663% which means that almost 99% of variation is caused by Household consumption. The adjusted R square is 98.6956% .The standard deviation of the
Residuals are 2.51283E9 the average value of the residuals is 1.43175E9. Also the Durbin-Watson (DW) statistic shows that, there isn't any serious autocorrelation in the residuals since this value came out to be greater than 1.4.
The model can no longer be simplified since the highest P value of any independent value is 0.0856, belonging to Quasi money. This value is less than 0.10 and so the variable is significant at the 90% or higher confidence level.
Ho: Monetary Policy insignificantly affects the saving of an individual.
H1: Monetary Policy significantly affects the savings of an individual.
As the probability is less than 0.10 we reject Ho. So, Monetary Policy significantly affects the savings of an individual.
Ho: Savings of individuals at or near retirement do not vary with changes in different types of financial assets.
H1: Savings of individuals at or near retirement vary with changes in different types of financial assets.
As the probability is more than 0.10 we do not reject Ho. So, Different types of assets have insignificant relation with savings.
Ho: Age group 15-65 has insignificant positive effect on the saving
H1: Age group 15-65 has significant positive effect on the saving
As the probability is less than 0.10 we reject Ho. So, Age group 15-65 has significant positive effect on the saving
4.1.2: Savings Results
Parameter
Estimate
Standard Error
T Statistic
P-Value
CONSTANT
-1.53812
5.65666
-0.271914
0.7918
Labor force
-1421.14
961.298
-1.47835
0.1734
Population ages 0-14
-1560.19
453.611
-3.439
0.0074
Money supply
0.002019
0.004890
0.412851
0.0894
Population ages 15-64
-2227.31
2356.5
-0.94515
0.0693
Population ages 65 above
6804.11
4434.64
1.5343
0.1593
Quasi money
0.0104581
0.006250
1.6731
0.1286
Taxes on income
-0.057866
0.02370
-2.4411
0.0373
Forms of assets
0.0128468
0.00923033
1.39181
0.2015
Source
Sum of Squares
Df
Mean Square
F-Ratio
P-Value
Model
1.05459E21
7
1.50656E20
209.01
0.0000
Residual
6.48711E18
9
7.2079E17
Total (Corr.)
1.06108E21
16
R-squared = 99.3886 percent
R-squared (adjusted for d.f.) = 98.9131 percent
Standard Error of Est. = 8.48994E8
Mean absolute error = 4.95178E8
Durbin-Watson statistic = 3.05962
Gross savings = -1.53812E10 - 1421.14*Labor force + 0.00201924*Money supply - 1560.19*Population ages 0 to 14 + 6804.11*Population ages 65 and above + 0.0104581*Quasi money - 0.0578666*Taxes on income -
2227.31*Population ages 15 to 64
4.1.2.1: Analysis
Equation shows that Labor force has negative relationship with Household consumption, Population of age 0-14 has a positive relationship which shows that this age group consume more. Population of age 15-64 has negative relationship because savings are high and consumption in low in this age group. Population 65 above has a positive relationship because consumption is high in this age group as saving will fall. Quasi money has a positive relationship and Taxes has negative relation.
The variable show a statistically significant relationship at a 99% confidence level. The ANOVA table depicts a P value less than 0.01 that supports my stance.
R square is 99.3886% which means that almost 99% of variation is caused by Savings. The adjusted R square is 98.9131%The standard deviation of the
Residuals is 8.48994E8. the average value of the residuals is 4.95178E8. Alao the Durbin-Watson (DW) statistic shows that , there isn't any serious autocorrelation in the residuals since this value came out to be greater than 1.4.
The model can no longer be simplified since the highest P value of any independent value is 0.0856, belonging to Quasi money. This value is less than 0.10 and so the variable is significant at the 90% or higher confidence level.
Ho: Monetary Policy insignificantly affects the consumption of an individual.
H1: Monetary Policy significantly affects the consumption of an individual.
As the probability is less than 0.10 we reject Ho. So, Monetary Policy significantly affects the consumption of an individual.
Ho: Income Tax insignificantly affects the consumption of an individual.
H1: Income Tax significantly affects the consumption of an individual.
As the probability is more than 0.10 we do not reject Ho. So, Income Tax insignificantly affects the consumption of an individual.
Ho: Life expectancy has insignificant effect on the consumption
H1: Life expectancy has significant effect on the consumption
As the probability is less than 0.10 we reject Ho. So, Life expectancy has significant effect on the consumption
Limitations
Data on real estate is, as mentioned, not a part of the dataset. This is unfortunate since real estate values cannot be assumed as equal for the individuals, or proportional to savings. Many people today invest and saves in form of real estate due to which it has become of significant importance for life cycle hypothesis. Due to this more accurate results could not be concluded. The assumption of retiree is taken age 65 and above, as the life expectancy ration is 75 years of age. So I have assumed that people retiree 10 years before life expectancy ratio, as many articles I have studied done the same. People savings were to decline towards zero at death. Although in reality it is passed on as an in heritance. So, also the capital gains from inheritance were also ignored.
Conclusion
It is concluded that Life-cycle Hypothesis compatible with the saving and consumption patterns of Pakistan. The life-cycle model did correctly predict that age, lifetime wealth, and interest rate effect household saving. The life-cycle hypothesis does however leave out important determinants, which I feel devalues the model. It is hard for me to assume variables such as race, location of residence, education, occupation, and a person's own personal outlook on the economy do not affect savings.
