Born To Be Destitute: Capital Transfer and Intergenerational Transfer of Poverty Augus Surachman
|
Characteristic | Information |
Origin Family | |
Number of children (average) Father origin family Mother origin family |
5.2 (sd=2) 4.8 (sd=1,9) |
Parent job Father’s parent Mother’s parent |
76.7% in agricultural sector 61.7% in agricultural sector |
Sample Family | |
Number of children (average) | 2.4 (sd=1,3) |
Father age (year) | 35.7 (sd=6,6) |
Mother age (year) | 32 (sd=5,7) |
Father job | 46.7% factory laborer |
Income average/month (Rp)
Poor family Not poor family |
1.650.500 (sd=1.149.253,9)
849.333,3 (sd=237.209,8) 2.451.666,7 (sd=1.141.421) |
Income average/capita/month (Rp)
Poor family Not poor family |
400.244 (sd=297.606,5)
218.305,6 (sd=91.071,27) 582.182,5 (sd=321.579,4) |
Both income average per month and income average per capita per month of all sample families (poor and not poor) were above West Java Province poverty line in 2010 (Rp201.138,00) and above $1 income per day per capita standard from World Bank (assumption $1=Rp9000,00). However, if we use another World Bank standard of $2 income per day per capita, only average income per capita per month of not poor sample family was above.
The observation toward origin of family welfare status showed that more than half of them were not poor, respectively 55 percent for father origin family and 51.7 percent for mother origin family. Welfare status of both generation families was compared to reveal the poverty dynamic status of father and mother. About 41.7 percent of fathers were categorized as always poor, while 46.7 percent of fathers were grouped into never poor category. The remaining 3.3 percent of fathers experienced out from poverty, and another other 8.3 percent claimed a move out from poverty. On the mother’s side, the poverty dynamic status was dominated by the always poor (41.7%) and never poor (43.3%). About 15 percent of mothers experienced status mobility (up and down), respectively 8.3 percent move into poverty and 6.7 percent out from poverty.
Marriage could be a possible alternative for someone to socially move up or down. In order to analyze the effect of marriage on social movement, origin of family welfare status of father and mother were compared with today’s sample family welfare status. The result showed all sample families were poor when they were formed by father and mother who came from poor family origins. On the other hand, when fathers from not poor families married mothers from poor families, half of that type of sample family was poor today. Conversely, when a poor father married a not poor mother, the majority of that type of sample family was poor today. This result indicated that the father’s origin of family welfare status was playing a bigger role in the determination of sample family welfare status today.
Table 2 Percentage of sample family welfare status based on father and mother origin family welfare status (n=60 families)
Origin Family of | Sample Family |
||
Father |
Mother |
Poor (%) |
Not Poor (%) |
Poor |
Poor |
100 |
0 |
Not Poor |
Poor |
50 |
50 |
Poor |
Not Poor |
67 |
33 |
Not Poor |
Not Poor |
4 |
96 |
This phenomenon could be explained by the fact that the father was the major money earner for the majority of sample families. The father origin family welfare status determined the ability of his parent to invest on his human capital aspect that determines father quality in the future. Then father quality plays a big role in determining the income that he and his family will earn that directly affects family welfare status.
Parental investment in children becomes the main way to transfer human capital to the next generation. Parental Investment on father and mother were approached by observation on parental investment behavior in father and mother on their early child and formal education that was attained by them.
Parental Investment behavior on father and mother. Generally, parental investment behavior scores in mothers (M=43.6; sd=4.4) were higher than parental investment in fathers (M=40.9; sd=5) and both statistically different (p<0.01). If it was analyzed based on welfare status of sample family, father and mother that are not poor today were invested more by their parents than today’s poor father and mother. This indicated the between parental investment and welfare status.
Father and mother formal education. Father attained longer formal education (M=9.7 years; sd=3.8 years) when compared with mother (M=8.4 years; sd=2.7 years) and both are statistically different (p<0.01). Father and mother from not poor family stayed at school longer than father and mother from poor family. Years of education of father from poor and not poor family were statistically different (p<0.01) and also in mother group (p<0.01).
Bequest is the main way for parents to transfer material capital to the offspring. For this study, the rate of fathers that received bequests (56.7%) was higher than mothers (26.7%). Fathers of not poor sample families that received bequests was higher than fathers of poor sample families. Although in the mother groups, the number of poor and not poor mothers that received bequests was equal. About 76.5 percent fathers and 50 percent mothers that received bequest were experiencing never poor of dynamic poverty status. Another interesting fact is that no sample family that experienced the move out from poverty status also received bequests from parents.
Table 3 Distribution of father and mother based on parental investment behavior score and sample family welfare status (n=60 families)
Parental investment behavior category |
Poor |
Not Poor |
Total |
|||
n |
% |
n |
% |
n |
% |
|
Toward Father |
|
|
|
|
|
|
Low |
8 |
26,7 |
1 |
3,3 |
9 |
15 |
Moderate |
21 |
70 |
25 |
83,3 |
46 |
76,7 |
High |
1 |
3,3 |
4 |
13,3 |
5 |
8,3 |
Total |
30 |
100 |
30 |
100 |
60 |
100 |
Average |
38,1 |
43,7 |
40,9 |
|||
Sd |
4,5 |
3,9 |
5 |
|||
Toward Mother |
|
|
|
|
|
|
Low |
1 |
3,3 |
1 |
3,3 |
2 |
3,3 |
Moderate |
28 |
93,3 |
22 |
73,3 |
50 |
83,3 |
High |
1 |
3,3 |
7 |
23,3 |
8 |
13,3 |
Total |
30 |
100 |
30 |
100 |
60 |
100 |
Average |
41,6 |
45,6 |
43,6 |
|||
Sd |
3,1 |
4,6 |
4,4 |
Two regression models were built to analyze factors affecting sample family welfare status. The first model was analyzed using logistic regression with family welfare status as the dependent variable (0=poor, 1=not poor). There were seven expected independent variables in the first model: father’s origin family welfare status, father’s years of education, score of parental investment in father, score of parental investment in mother, bequest received status of father, bequest received status of mother, and father age. Model was statistically significant (chi square=791; p<0.000df=7), and Neglekerke R Square of the model was 0.862 – indicated strong relation between prediction and grouped sample. The predicted success rate of the model was 91.7 percent (90% to be poor and 93.3% to be not poor).
Independent variables that were statistically affected on the sample family welfare were father origin family welfare status (p<0.05), father’s years of formal education (p<0.05), and parental investment behavior toward mother (p<0.05). The probability of sample families in which the father came from a poor family was 38 times higher to be poor than sample families in which the father came from not poor family origins. In addition, every year of improvement of the father’s formal education will increase twice the probability of sample family to be not poor. Then every point of improvement of parental investment behavior score toward mother will increase 1.5 times the probability of the sample family to be not poor.
Table 4 Summary of logistic regression to analyze factors affected sample family welfare status (n=60 keluarga)
Independent Variables |
Sample Family Welfare Status (0=poor, 1=not poor) |
|
B |
Exp (B) |
|
Constant |
-43,767 |
0,000 |
Father origin family welfare status (0=poor, 1=not poor) |
3,639 |
38,052** |
Father formal education (years) |
0,728 |
2,071** |
Parental investment behavior toward father (score) |
0,070 |
1,073 |
Parental investment behavior toward mother (score) |
0,419 |
1,521** |
Father bequest received status (0=no, 1=yes) |
3,222 |
25,088 |
Mother bequest received status (0=no, 1=yes) |
1,252 |
3,499 |
Father age (years) |
0,223 |
1,249 |
|
62,791 |
|
|
0,862 |
Note: **= statistically significant at the 95% level
Meanwhile, another model was analyzed using multiple linear regressions with family income as the dependent variable (as the approach to family welfare status). In this analysis, there were two models built, unrestricted and restricted model. The unrestricted model was built by employing all independent variables that theoretically affected dependent variable and ignored correction aspect of linear regression analysis. Regarding the multicolinearity issues, some variables were dropped out from the unrestricted model for resulting restricted model. Then R-square value of both models was compared to analyze the reliability of the model.
There were eight independent variables of the unrestricted model that were statistically significant (p<0.01; F=5.782). The value of R-square of the unrestricted model was 0.476 with no independent variable statistically affected family income. Then three variables were dropped out from the model and the five remaining independent variables were father family of origin, family welfare status, parental investment behavior toward mother, father formal education, and father bequest received status. The restricted model that was also statistically significant (p<0.001; F=12.241), and the R-square value of the model was 0.471. The difference of R-square value between both unrestricted and restricted was very small. In other words, the restricted model was as reliable as unrestricted model on explaining factors affecting family income, although some independent variables were dropped out from the model. Variables that significantly affected sample family income were father’s origin family welfare status (P<0.05) and father’s formal education (p<0.01). Every year of improvement of the father’s formal education will increase the income of sample family income with Rp122.205,071.
Table 5 Summary of multiple linear regression to analyze factors affected family income (n=60 families)
Independent Variables |
Model |
|||
Unrestricted |
Restricted |
|||
B |
β |
B |
β |
|
Constant |
-2,060E6 (1,645E6) |
|
-1,665E6 (1,170E6) |
|
Father origin family welfare status (0=poor, 1=not poor) |
688109,993 (416970,744) |
0,300 |
774714,618 (307503,228) |
0,338** |
Mother origin family welfare status (0=poor, 1=not poor) |
69997,437 (297444,070) |
0,031 |
|
|
Parental investment behavior toward father (score) |
5690,236 (42706,095) |
0,025 |
|
|
Parental investment behavior toward mother (score) |
30236,625 (36533,157) |
0,115 |
19984,965 (29337,312) |
0,076 |
Father formal education (years) |
133425,559 (53596,244) |
0,441 |
122205,072 (39359,094) |
0,404*** |
Mother formal education (years) |
-43589,364 (68367,484) |
-0,103 |
|
|
Father bequest received status (0=no, 1=yes) |
3634,324 (317092,161) |
0,001 |
-38124,194 (284951,679) |
-0,015 |
Mother bequest received status (0=no, 1=yes) |
-123212,328 (367178,559) |
-0,037 |
|
|
F |
5,782*** |
12,241*** |
||
R-square |
0,476 |
0,471 |
||
Adjusted R-square |
0,393 |
0,432 |
Note:
B = Unstandardize coefficient (standard error is in parenthesis)
Β = Standardize coefficient
*= statistically significant at the 90% level
**= statistically significant at the 95% level
***= statistically significant at the 99% level
The reduction of number of children between origin and sample family indicated the success of the family planning program as a government program for about three decades. Research conducted by Herarti (2004) in Sumedang and Subang showed that small family norms with two children as the part of family program in Indonesia had been adopted. However, sample families in this research had not finished their family cycle yet. Thus it is possible for sample families to have another child. Besides number of children, change was also showed in the job sector. The decrease of families that rely on their income stream from agricultural sector was the consequence of the general social structure change in the society.
This research also indicated the existence of intergenerational transfer of poverty in two-generation families. Sample family grouping based on welfare status, into poor or not poor, gave insight related to poverty transfer mechanism utilizing intergenerational capital transfer approach. Further, regression analysis revealed that formal education (especially for father) as part of parental investment in child plays a big role on sample family welfare status. This result supports the previous study result from Siregar and Wahyuniarti (2008) and also Chaudry et al. (2010) about negative effect of formal education on poverty level.
There is need to highlight the phenomenon related to marriage and sample family welfare status. The majority of sample families were formed by couples from the same social economic status, so we can explore father’s and mother’s origin family welfare status. Most poor sample families consisted of father and mother that originally came from poor families. Conversely, most not poor sample families were filled by father and mother that came from not poor families. In other words, there was a tendency of similar social status marriage in sample families. In Sociology, this phenomenon is known as homogeny (Collins & Coltrane, 1996).
Only a small number of fathers and mothers experienced welfare changes in this study (move into poverty or out from poverty). Regarding the sociological term, they experienced what was called as social mobility. A sample in this group could further divide into two groups: the first group consisted of sample families that experienced downward mobility (move into poverty); another group filled by sample families that experienced upward mobility (out from poverty). In the case of the sample that experienced upward mobility, it was not related to material transfer through bequest because originally they came from poor family origins. For fathers who experienced upward mobility status, the regression analysis proved that higher formal education level played a big role. In contrast, for mothers, education seems not to be the main factor that boosted them to move upward. If we explore further, mothers that came out from poverty status were married to husbands with higher social status.
Actually, the same phenomenon was also found in the case of fathers. But for a father to be married to a wife with higher social status, higher formal education level appears to be the absolute requirement, although it was not in the mother’s case. In other words, we can conclude that a mother or woman has a tendency to be socially more mobile than father or man through marriage. Chen et al. (2009) explained this phenomenon as the result of what is referred to as the Cinderella effect. A woman’s position to be admired in the marriage market was less determined by social economic characteristics such as wealth or income. Some research revealed that the factor most commonly considered by a man in choosing a woman on the marriage market was physical appearance of the woman. Conversely, the woman gives more consideration to income and education level of the man. Collins and Coltrane (1996) explained that men act based on their spontaneous feelings of love when selecting partner. While for women, marriage will be very important for their social economic status, thus the majority of women do what is called “emotional work.” Women “direct” and “shape” their feelings to choose the man that is considered as “Mr. Right.”
Beyond that, parent-child interaction effects on welfare status was the most important factor to be highlighted. Regression analysis revealed that sample family welfare status was affected by parental investment in children, whether through parental investment behavior in their early age or formal education. That result is consistent with Leibowitz’s (1988) findings, where income of someone in the future was determined by education level and early age experience. Thus we can conclude that parental investment in children was a determinant of welfare in the future.
As mentioned earlier, the concept of investment in human capital seems like a two-sided sword for the poor group. It is clearly the solution for them to move out from poverty, but on the other hand it also seems like a problem for them because of the limitation of resources in order to accomplish it. According to Schiller (2008), the role of the external environment, especially the government, is very important to answer the problem. Poverty eradication programs should help poor families to invest more toward their offspring, especially on education.
Poverty eradication programs in Indonesia today, such as Program Keluarga Harapan (PKH) are moving in this direction, helping poor families to invest more in their offspring. However, there is still less attention toward the possibility of what Schiller (2008) called flawed character that is reflected from the culture of poverty. According to Moore (2001), the culture of poverty has also affected the existence of intergenerational transfer of poverty. Research conducted by Simanjuntak (2010) about money allocation by a family as the target of Program Keluarga Harapan from 2008 until 2009 showed that allocations of aid funds for investment in children were less and the highest portion was for material asset purchase. In the future, there must be a policy breakthrough to answer that issue, such as integrating family finance management guidance with that program.
Bottema, T., Masdjidin, S., & Madiadipura, H. 2009. Family life history as a tool in the study of long-term dynamics of poverty: an exploration. Di dalam: Rusastra, Pasaribu, Yusdja Y. Editor. Land and Household Economy 1970-2005. Bogor: Indonesian Center for Agriculture Socio-Economic and Policy Studies.
Chaudhry, I. S., Malik, S., Hassan, A., & Faridi, M. Z. 2010. Does education alleviate poverty? Empirical evidence from Pakistan. IRJFE: Issue 52 (2010).
Chen, J., Avise, J., Lamb, B., Salathe, E., Mass, C., Guenther, A., Wiedinmyer, C., Larmargue, J.-F., O'Neill, S., McKenzie, D.,& Larkin, N., 2009: The effects of global changes upon regional ozone pollution in the United States. Atmos. Chem. Phys., 9, 1125-1141.
Collin, R., & Coltrane, S. 1995. Sociology of Marriage and The Family: Fourth Edition. Chicago: Nelson-Hall Publishers.
[CPRC]. Chronic Poverty Research Center. 2008. Escaping poverty traps. The Chronic Poverty Report 2008-09.
Hartoyo. 1998. Investing in children: study of rural families in Indonesia. [Disertasi]. Blacksburg: Virginia Tech University.
Herarti, R. 2004. Family planning decision-making: case studies in West Java, Indonesia. The 12th Biennial Conference of the Australian Population Association.
Leibowitz, A. 1982. Home investment in children. Economics of the Family: Marriage, Children, and Human Capital. Editor: Theodore W. Schultz. Chicago: The University of Chicago Press.
Moore, K. 2001. Frameworks for understanding the intergenerational transmission of poverty and well-being in developing countries. CPRC: Working Paper 8.
______ . 2005. Thinking about youth poverty through the lenses of chronic poverty, life-course poverty and intergenerational poverty. CPRC Working Paper 57.
Pakpahan, Y. M., Suryadarma, D., & Suryahadi, A. 2009. Destined for destitution: intergenerational poverty persistence in Indonesia. Jakarta: SMERU Research
Schiller, B. R. 2008. The Economics of Poverty and Discrimination. New Jersey: Prantice Hall.
Simanjuntak, M. 2010. Faktor-faktor yang mempengaruhi kesejahteraan keluarga dan prestasi belajar anak pada keluarga penerima Program Keluarga Harapan (PKH). [Tesis]. Bogor: Fakultas Ekologi Manusia, Institut Pertanian Bogor.
Sirega,r H., & Wahyuniarti D. 2008. Dampak pertumbuhan ekonomi terhadap penurunan jumlah penduduk miskin. Di dalam: Yusdja et al., editor. Peran Sektor Pertanian dalam Penanggulangan Kemiskinan. Bogor: Pusat Analisis Sosial Ekonomi dan Kebijakan Pertanian.
Wagle, U. 2008. Multidimensional Poverty Measurement: Concepts and Applications. New York: Springer.
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