Gender assets shocks_ifpri bbl may 2011

677
-1

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
677
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
8
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Gender assets shocks_ifpri bbl may 2011

  1. 1. Do Men and Women Accumulate Assets in Different Ways? Evidence from Rural Bangladesh Agnes Quisumbing International Food Policy Research Institute May 2011 Tuesday, June 21, 2011
  2. 2. Introduction• This paper attempts to bring together two threads of the literature on assets:• (1) literature on asset dynamics and poverty traps (Carter and May; Carter and Barrett; others)• (2) literature on risk and intrahousehold allocation, that suggests that risk are not pooled within the household• Earlier work on (1) using data from Bangladesh focused on hh asset dynamics; found no evidence for multiple poverty traps, possibly because of reasonably well- functioning factor markets (labor and credit markets, although credit markets may discriminate against the landless)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 2
  3. 3. Why look at gender-differentiated asset dynamics?• General: evidence that risk is not pooled within households (Ethiopia—Dercon and Krishnan; Cote d‘Ivoire—Dulfo and Udry; Ghana—Goldstein) and that risk perceptions may also differ between men and women (East Africa--Doss, McPeak, Barrett)• There is also evidence rejecting unitary model of the household in many countries and specifically for Bangladesh—resources are not pooled within the household• Social norms favoring female seclusion lead women to be systematically excluded from labor markets in Bangladesh• Anthropological evidence (Thailand, Indonesia, Bangladesh) suggests that men and women have different asset accumulation strategies, and use their assets in different ways to cope with shocks INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 3
  4. 4. Research questions• Are asset dynamics different for joint and exclusively- held assets? How do these differ from household asset dynamics?• Is the impact of negative events and processes (flood shocks, dowries, illness, death) different on husband-, wife- and jointly-owned assets? Are these mitigated by positive events?• …And a policy-related question• What are the implications for the design of social protection systems?INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 4
  5. 5. Presentation overview1. Conceptual framework and methods2. Survey design and data • Assets and traps:The CPRC-DATA-IFPRI longitudinal study • Gender and assets: The agricultural technology panel3. Descriptives4. Nonparametric results5. Parametric results6. Concluding remarksINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 5
  6. 6. Conceptual framework• Barrett, Carter, others: theory of dynamic poverty traps, empirically tested using data from SSA• Based on observation that it is easier to measure assets than consumption expenditure or income• Parametric and nonparametric methods used to derive a dynamic asset frontier, showing relationship between hh asset holdings in two periodsINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 6
  7. 7. At+1 At= At+1 f(At) At AL A* AH
  8. 8. • AL: stable low level equilibrium• A*: unstable mid-level equilbrium• AH: stable high level equilbrium• Prediction is that hh‘s asset trajectories will bifurcate, with hh‘s with A>A* tending toward the high level equilibrium, and those with A<A* tending to the low level equilibrium• Some hhs will tend toward a chronically poor state, and others toward relative affluenceINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 8
  9. 9. How to estimate the dynamic asset frontier?• Nonparametric methods: we use locally- weighted scatterplot smoothing (Lowess) (Cleveland 1979)• Parametric methods: use a linear term in lagged assets, plus higher order terms to allow curvature• What is different in this paper: we estimate this for husband-owned, wife-owned, and jointly owned land and nonland assetsINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 9
  10. 10. General empirical specification• We estimate the following nonparametrically:• At+1 = ß (At) + εt• The analogous parametric regression is:• At+1 = (1 + α)At + θt, which is estimated in differenced form as• At+1 - At = αAt + θt• Dynamic equilibrium: at least in expectation, asset stocks do not change over time, that is,• E[At+1 - At ] =0• Condition for dynamic eqbm at A*:- 2 < ∂ E[At+1 - At ]/ ∂ At │A* ≤ 0INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 10
  11. 11. Empirical specificationAit-AiB= ß0 + ß1 AiB + ß2AiB2 + ß3AiB3 + ß4AiB4+ ZiΓi + CiΛi + εitAit -ln AiB asset growth for asset owner i from baseline survey period (B) to the most recent survey (T)AiB assets at baselineZi and Ci are time invariant individual, household, and community characteristics and ε­it is the error termTests for convergence: tests on coefficientsINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 11
  12. 12. Survey design and dataINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 12
  13. 13. Assets and traps: The CPRC-DATA-IFPRI Study--1• Longitudinal study seeks to examine factors behind movements out of poverty over the long- term, as well as factors that make some households and individuals unable to escape poverty• Builds on three evaluations undertaken by DATA and IFPRI • Microfinance (MFI) from 1994 • Agricultural Technology (AT) from 1996 • Educational Transfers (ET) from 2000INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 13
  14. 14. The CPRC-DATA-IFPRI Study--2 • A qualitative and quantitative methods study with 3 phases: • Summer 2006: focus group discussions investigating causes of decline and improvement and the long term impact of 3 interventions (116 FGDs in 11 districts) • Winter 2006-7: quant resurvey of panel households (1787 core + 365 splits) • Spring-Summer 2007: life history interviews and village histories in 8 districts (160 households – 300 interviews)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 14
  15. 15. Map of study sites of longitudinal study Page 15
  16. 16. Agricultural technology study: 1996-1997 • Only site with gender-disaggregated asset data at baseline • 3 technologies/implementation modalities: 1. improved vegetables for homestead production, disseminated through women‘s groups (Saturia) 2. fishpond technology through women‘s groups (Jessore) 3. fish pond technology targeted to individuals (Mymensingh)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 16
  17. 17. Page 17
  18. 18. To recap: Survey design and sampling• Panel data set with gender disaggregated data includes 904 core households previously surveyed by DATA and IFPRI in 1996-97, as well as household splits; estimation sample is smaller (725 hhs with complete information on husband and wife)• Core households are those that were interviewed in baseline and 2006/7 rounds• Split households are those formed by children who formed separate residences (tracked within district)—not included in this analysisINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
  19. 19. Attrition• Attrition is relatively low: 93.7 percent of original households were reinterviewed, and the attrition rate is about 0.4 percent per year in the agricultural technology site• Attrition rates for hhs are about 4-11% for households across interventions, but for ―intact couples‖ attrition is higher, 17% (over a 10-year period)• To account for attrition, all regressions estimated with inverse probability weights (Fitzgerald, Gottschalk, Moffitt 1998)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
  20. 20. Poverty and poverty transition categories Agricultural technology (1996-2006) Poverty headcount Poverty in baseline 70% survey Poverty in 2006/2007 18% Poverty transitions Chronic poor 16% Falling into poverty 2% Moving out of poverty 54% Never poor 28%INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
  21. 21. Asset growth of core households over time Asset holdings Household assets Value (‗1000 taka, 2007 prices) 1996 2006 Annual growth rate Total nonland assets 27.0 49.7 8.4 Consumer durables 8.13 15.8 9.4 Ag durables 4.8 1.5 -6.9 Nonag durables 1.2 4.4 25.8 Jewelry 2.5 11.1 35.2 Livestock 10.5 17.0 6.3 Total owned land (decimals) 148.5 117.4 -2.1INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 22
  22. 22. Asset growth over time , 1996 and 2006 (exclusively held assets) 1996 2006 % change H W H W H W Landholdings (decimals) Homestead 10.3 .3 10.9 0.6 5.8 44.5 Cultivated 85.9 1.9 67.9 3.2 -21.0 39.7 Other land 5.4 .1 5.0 0.2 -8.9 6.1 Total owned land 101.7 2.4 83.8 4.0 -17.6 39.2 Nonland assets („000 taka, 2007 prices) Consumer durables 2.2 .3 5.8 0.4 166.4 40.8 Ag durables 1.6 n.s. 0.6 n.s. -62.7 6.2 Nonag durables 0.5 n.s. 3.3 0.1 494.3 428.9 Jewelry n.s. 1.5 1.5 2.1 5262.2 38.5 Livestock 5.8 1.7 9.1 1.1 57.5 -31.9 Nonland assets (excl 4.4 1.8 11.2 2.6 155.3 42.1 livestock)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 23
  23. 23. Distribution of area of owned land across ownership categories 1996 2006 Joint Joint Husband Husband Wife WifeINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 24
  24. 24. Distribution of nonland assets across ownership categories 1996 2006 Joint Joint Husband Husband Wife WifeINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 25
  25. 25. Most common shocks experienced by households, 1996- 2006INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
  26. 26. Proportion of households reporting negative shocks, 1997-2001 and 2002-2006 50 45 40 35 30 Illness, 1997-2001 Proportion of 25 households Illness, 2002-2006 20 Death, 1997-2001 Death, 2002-2006 15 Dowry and wedding, 1997-2001 10 Dowry and wedding, 2002-2006 5 0 Illness, Illness, Death, Death, Dowry and Dowry and 1997-2001 2002-2006 1997-2001 2002-2006 wedding, wedding, 1997-2001 2002-2006 Type of negative shockINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 27
  27. 27. Proportion of households reporting positive events, 1997-2001 and 2002-2006 9 8 7 6 5Proportion of households 4 Remittances, 1997-2001 3 Remittances, 2002-2006 2 Inheritance, 1997-2001 Inheritance, 2002-2006 1 Dowry received, 1997-2001 0 Dowry received, 2002-2006 Type of positive eventINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 28
  28. 28. Parametric specificationAit-AiB= ß0 + ß1 AiB + ß2AiB2 + ß3AiB3 + ß4AiB4+ ZiΓi + CiΛi + εitDependent var: Asset growthRegressors: Lagged assets (linear, squared, cubed, fourth)Covariate shocks (floods)Idiosyncratic shocks (illness, death, dowry/wedding expenses)Positive events (remittances, inheritance, received dowry)HH demographic characteristics: age of head, age squared, hh size, proportion in age-sex categoriesValue of (assets) land at baseline [assets in land equation; land in assets equation)Thana dummiesINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 29
  29. 29. Results Page 30
  30. 30. Lowess plots for land (scale of axes not uniform across graphs) Household land Jointly-held land 2000 1000 800 1500 Joint Land 2007 Own Land 2007 600 1000 400 500 200 0 0 0 500 1000 1500 0 500 1000 1500 2000 Own Land 1997 Joint Land 1997 Husband’s land Wife’s land 1500 150Own Land Husband 2007 1000 Own Land Wife 2007 100 500 50 0 0 0 500 1000 1500 0 50 100 150 Own Land husband 1997 Own Land Wife 1997
  31. 31. Lowess plots for nonland assets150000 Household Jointly-held assets 150000 Value of Joint Assets 2007100000 100000 50000 50000 0 0 0 50000 100000 150000 0 50000 100000 150000 Value of Assets 1996 Value of Joint Assets 1996 Husband’s assets Wife’s assets150000 150000100000 Value of Wife Assets 2007 100000 50000 50000 0 0 0 50000 100000 150000 0 50000 100000 150000 Value of Husband Assets 1996 Value of Wife Assets 1996
  32. 32. Parametric results: Land• Initial landholdings matter for jointly-owned and wife- owned land but not husband-owned land (acquired mostly through inheritance)• Individual and hh characteristics significant for husband- owned land: wife‘s schooling (+), proportion of older males at baseline (+), nonland assets (+)• Very few individual and household characteristics affect growth of joint- and wife-owned land; wife owned land is affected by wife‘s schooling (-) and location (Jessore +)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 33
  33. 33. Parametric results: Nonland assets• Initial assets matter for joint and husbands‘ assets, but not wife‘s assets• Baseline characteristics matter:• Joint assets: higher levels of schooling (+), demographics• Husbands‘ assets: hh size (-), wife‘s schooling (+)• Wife‘s assets: age and age squared (life cycle factors)• Location dummies importantINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 34
  34. 34. Impact of shocks on exclusively held land is not symmetric Shocks and positive events Land Joint Husbands Wives “Earlier shocks” 97-01 Death 97-01 Dowry and wedding Positive (weak) 97-01 Dowry receipts Negative (weak) “Later shocks” 02-06 Death Negative Positive (weak) 02-06 Remittances Positive (weak) 02-06 Dowry receipts NegativeINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 35
  35. 35. Impact of shocks on exclusively held nonland assets is not symmetric either Shocks and positive events Nonland assets Joint Husbands Wives “Earlier shocks” 97-01 Floods Negative (weak) 97-01 Illness Positive (weak) 97-01 Dowry and wedding Negative 97-01 Inheritance Positive Positive “Later shocks” 02-06 Illness Negative Negative (weak) 02-06 Death Negative 02-06 Dowry and wedding Positive 02-06 Remittances Positive 02-06 InheritanceINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Negative Negative Page 36
  36. 36. Life-cycle events are clearly important determinants of asset accumulation and decumulation• Dowry and wedding expenses reduce husbands‘ assets (dowry receipts increase joint assets, but reduce wife‘s assets)• Death reduces husband‘s assets• Early inheritance increases assets, later inheritance reduces it (associated with a death, or property division)• Remittances associated with children growing up and working tend to increase joint assets• Question: are there better ways to prepare for (save for?) these life-cycle events?INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 37
  37. 37. Impact of shocks on husband-wife growth differs by type of asset and type of shock Shocks and positive events Land Nonland (ΔH -Δ W) assets (ΔH -Δ W) Floods 97-01 Illness 97-01 Death Wife (+) 97-01 Dowry and wedding Wife (+) 97-01 Remittances Wife (+) 97-01 Inheritance Husband (+) “Later shocks” 02-06 Illness 02-06 Death Wife (+) 02-06 Dowry and wedding 02-06 Remittances 02-06 InheritanceINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Wife (+) Page 38
  38. 38. Familial networks matter, but not in the same way Land Nonland assets Joint Husband Wife Joint Husband Wife Husband‘s Negative brothers Husbands Negative Positive sisters Distance to Positive husband‘s village Wife‘s Negative brothers Wife‘s sisters Distance to Negative Negative wife‘s villageINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 39
  39. 39. Conclusions--1• Very interesting evidence on gender-differentiated asset growth over a decade• Asset growth positive for men and women, but faster for men (less unequal when looking at jointly held assets)• Raises questions about control of jointly held assets• Composition of men‘s and women‘s asset portfolios also changing as households diversify into non-agriculture, and as women get more involved in agriculture (possibly owing to NGO interventions)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 40
  40. 40. Conclusions--2• Shocks appear to have differential impacts--women‘s assets are negatively affected by illness, men‘s by death, illness, and dowry and wedding expenses• Illness is the shock most frequently reported by households=>implications for asset disposal?• Life-cycle events (dowries, weddings, death) important, how to better prepare for them?• This analysis has also been done for disaggregated assets, indicates that there is a lot of movement in consumer durables and agricultural durables, also livestock and jewelryINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 41
  41. 41. Implications--1• Need to devise social protection strategy to provide insurance against shocks• Health insurance may help protect asset stocks (as well as individual health)• Social safety nets (public works, income transfer programs) may help prevent asset depletion, which would also help protect future livelihoods• What to do with dowries? Good question!• Important to increase incentives to invest in women‘s human capital as well as to increase returns to human capital (e.g. remove barriers to labor market participation)INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 42
  42. 42. Implications--2• Need to provide mechanisms for poor to save and build up asset stocks, and to rebuild them after shocks• Need to provide mechanisms to prepare adequately for (anticipated) life-cycle events• Women, in particular, need to be able to build up assets (savings?) that they can controlINTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 43
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×