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Worker Household Living Standards and Income Inequality in State Forest Areas of the Northeast China Yuanyuan Yi and Jintao Xu PhD candidate, University.

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Presentation on theme: "Worker Household Living Standards and Income Inequality in State Forest Areas of the Northeast China Yuanyuan Yi and Jintao Xu PhD candidate, University."— Presentation transcript:

1 Worker Household Living Standards and Income Inequality in State Forest Areas of the Northeast China Yuanyuan Yi and Jintao Xu PhD candidate, University of Gothenburg, Sweden; Professor, Peking University, China Annual World Bank Conference on Land and Poverty Washington, D.C., March 25 th, 2014

2 Outline 1.Introduction 2.State Forest Areas in the Northest China 3.Data 4.Empirical strategy 5.Empirical results and discussions 6.Conclusions

3 1. Introduction Motivation: 1.China’s rapid economic growth and income gap between rural and urban areas, overall income inequality 2.Economic measures of living standards: consumption- or income-based 3.Random or systematic error when collecting household income or consumption data (Deaton and Zaidi, 2002) Objective: 1.Correcting random/systematic error in household income through aggregating present value of consumer durables and housing into total household income 2.Descriptive analysis of worker households’ income from different sources and relative importance of each source 3.Trends and patterns of worker household income distribution, in various categories, and how percentage change in one specific source of income influence the distribution of income

4 2. State Forest Areas in the Northeast China Since 1986, central government undertaken solutions specifically for state-owned forestry enterprises Natural Forest Protection Project since 1998 In 2008, further steps, setting Northeast China as the key region for reforming the current forest resource management systems Workers in state forest areas with lower income than urban counterparts, but much higher costs of basic living expenses than rural households

5 3. Data Environmental Economics Program in China, Peking University (EEPC) Two rounds survey in 2005 and 2009 Table 1. Time of the surveyProvince Management BureauForest BureauHousehold 2005.06-07Heilongjiang415912 2005.07Jilin26364 2005.09Inner Mongolia13180 2009.07-08Heilongjiang415720 2009.07Jilin26256 2009.06Inner Mongolia13109 Total37241456/1085

6 Table 2. Sample demographic information Full sampleMountain top-dwellersMountain base-dwellers 199720042008199720042008199720042008 Total Observations1455 1084726 569729 515 Hukou * (Permanent residence) Urban 1,309 (99%) 1,102 (99.1%) 1,019 (98.7%) 653 (99.2%) 557 (98.9%) 537 (98.3%) 656 (98.9%) 545 (99.3%) 482 (99.2%) Rural 9 (0.8%) 7 (0.6%) 11 (1.1%) 4 (0.6%) 4 (0.7%) 7 (1.3%) 5 (0.7%) 3 (0.6%) 4 (0.8%) No hukou3 (0.2%)3 (0.3%)2 (0.2%)1 (0.2%)2 (0.4%) 2 (0.3%)1 (0.1%)0 Household size Mean3.43.2 3.33.2 3.43.2 1 12 (0.8%) 25 (1.7%) 40 (3.7%) 9 (1.2%) 13 (1.8%) 17 (3%) 3 (0.4%) 12 (1.7%) 23 (4.5%) 2-3 960 (66%) 1,029 (70.7%) 719 (66.3%) 487 (67.1%) 527 (72.6%) 382 (67.1%) 473 (64.9%) 502 (68.9%) 337 (65.4%) >=4 483 (33.2%) 401 (27.6%) 325 (30%) 230 (31.7%) 186 (25.6%) 170 (29.9%) 253 (34.7%) 215 (29.4%) 155 (30.1%) Average age of adults per household Mean394045383944414246 Average of education per household Mean6.36.77.95.76.37.66.97.18.2 Below junior high 364 (51.1%) 421 (45.3%) 220 (29%) 201 (58.8%) 223 (51.3%) 117 (30.2%) 163 (43.9%) 198 (40%) 103 (27.8%) High school 236 (33.1%) 294 (31.6%) 248 (32.7%) 108 (31.6%) 136 (31.3%) 147 (37.9%) 128 (34.5%) 158 (31.9%) 101 (27.3%) Beyond college 113 (15.8%) 215 (23.1%) 290 (38.3%) 33 (9.6%) 76 (17.4%) 124 (31.9%) 80 (21.6%) 139 (28.1%) 166 (44.9%) Missing742525327384291182358234145 Total worker per household Mean2.22.12.32.22.12.32.122.2

7 Figure 1. Per capita income change

8 4. Empirical strategy Descriptive analysis of income from different sources and relative contributions to overall inequality Total household income aggregates: 1.Income from different sources 2.Present value of consumer durables 3.Present value of housing Income inequality decomposition rules (Lerman and Yizhaki, 1985) – decomposion of Gini coefficient A general regression-based approach – an earnings equation using an OLS estimation

9 5.1. Results from the regression-based approach Full sampleMountain top-dwellersMountain base-dwellers Dependent variable: three-year averages of per capita income Coefficient Inco me shar e Gini coefficient share (0.411) Coefficien t Income share Gini coefficie nt share (0.419) Coefficient Income share Gini coeffic ient share (0.402 ) Household size -635.5 ***-0.42-0.000028-589.6 **-0.39-0.006-703.2 **-0.49-0.001 (205.9)(283.7)(310.8) Average age 6.40.040.002-14.6-0.06-0.00529.9 *0.180.015 ( 13.8 ) (24.3)(15.1) Males as % of workers 2681.0 ***0.310.0061844.60.190.0043484.5 ***0.410.003 (966.5)(1621.9)(1168.8) Average education of adults 494.8 ***0.800.028701.8 ***1.040.055349.8 **0.680.017 (111.3)(159.3)(165.5) Number of members holding jobs -16.7-0.05-0.0008-190.6-0.120.006480.20.040.002 (285.1)(436.3)(445.7) Land per capita 20.4 ***0.44-0.42120.5 ***0.75-0.616-299.3 **-0.140.145 (1.3) (117.7) Number of plots -546.3-0.06-0.005-667.3 *-0.10-0.001-1415.6 *-0.01-0.003 (281.3)(368.9)(736.7)

10 Results from the regression-based approach, by quantiles Bottom 25%Second: 25%-50%Third: 50%-75%Top 25% Coefficient Robust Std.Err. Coefficient Robust Std.Err. Coefficient Robust Std.Err. Coefficient Robust Std.Err. Household size -125.2106.9-170.1118.989.688.3-1229.91022.9 Average age -0.97.913.6 ***3.6-13.6 **6.2-29.249.4 Males as % of workers 1675.0 **662.5590.2 *305.7-230.7419.5-657.52861.9 Average education of adults 1.252.0-52.044.2-32.139.7-152.3464.1 Number of members holding jobs -214.5192.4139.3123.1326.4 ***104.4690.31216.5 Land per capita -7.729.10.010.4-0.021.318.6 ***1.7 Number of plots 176.7260.3-188.0130.3-158.994.01962.33353.9 Communist Party member..669.9 *357.9-37.0254.64711.4 **2204.3 Cadre, (farm or bureau or higher) -716.6 **229.7-362.9348.1-250.0264.7-999.11676.8 Constant 1044.11315.72782.3 ***435.14519.3 ***534.216881.6 **7545.5 Provincial dummies Yes Adjusted R-square 0.41270.57160.35890.8549

11 5.2. The Gini decomposition for household income inequality Table 5. Gini inequality indices, by total, per capita income, and sources Income sourceYearObs.Total Per capitaEarnedAgriculturalForestryLivestockFinancialSocial Ins.TransferDurablesHousingOther Full sample 19971,455 0.5390.5470.7120.9570.9990.9910.9710.7910.9510.578.0.938 20041,455 0.5110.5190.7020.9620.9990.9810.9540.7340.9050.5850.5970.917 20081,084 0.4120.4080.5610.9380.9790.9991.0150.7030.7490.6480.6350.812 Mountain top-dwellers 1997726 0.5650.5690.730.9220.9990.9840.9760.8110.9530.58.0.945 2004726 0.5530.5590.7010.930.9970.9660.9490.7670.9130.5590.5770.937 2008515 0.430.4150.5450.8840.9630.9940.9470.730.7670.6580.6780.835 Mountain base-dwellers 1997729 0.5070.5180.6920.991.0.9950.9590.7620.9470.575.0.93 2004729 0.4640.4740.7040.993.0.9960.9580.6890.8950.6090.5610.893 2008569 0.3910.40.5750.9960.9970.9981.1170.6660.7290.6260.5730.784

12 From table 5 The Gini coefficient of per capita income is decreasing. Slightly different if looking at Gini coefficient of per capita income. Durables and Housing are relatively equal comparing to other sources. In each observed year, except for agriculture, livestock, finance, and durable goods, the Gini coefficient of the mountain top-dwellers was higher than that of mountain base-dwellers by each income source. Decomposition of the Gini coefficient by sources unravels contribution of each source of income to the overall inequality. We use the decomposition method proposed by Lerman and Yitzhaki (1985) and Abdelkrim and Duclos (2007)’s Stata package (DASP) on distributive analysis.

13 Contribution to total income inequality, by source Source 199720042008 EarnedFull sample 0.5770.4610.471 Mountain top-dwellers 0.5910.440.404 Mountain base-dwellers 0.5690.490.559 Agriculture Full sample 0.010.0610.14 Mountain top-dwellers 0.0280.1120.235 Mountain base-dwellers -0.0010.0020.013 Financial Full sample 0.0550.0260.053 Mountain top-dwellers 0.090.0240.056 Mountain base-dwellers 0.03 0.049 Transferred Full sample 0.005-0.001-0.0001 Mountain top-dwellers 0.003-0.0030.002 Mountain base-dwellers 0.006-0.001-0.003 Durables Full sample 0.0090.0120.023 Mountain top-dwellers 0.0090.0080.025 Mountain base-dwellers 0.0130.0170.02 Housing Full sample. 0.0080.007 Mountain top-dwellers. 0.0030.006 Mountain base-dwellers. 0.0120.008

14 Marginal effect on total income inequality, by source Source 199720042008 EarnedFull sample 0.0460.022-0.012 Mountain top-dwellers 0.0560.005-0.037 Mountain base-dwellers 0.0410.0480.026 Agriculture Full sample -0.0060.0150.05 Mountain top-dwellers -0.0070.0230.075 Mountain base-dwellers -0.002-0.0010.006 Financial Full sample 0.0160.0040.025 Mountain top-dwellers 0.0260.0010.024 Mountain base-dwellers 0.009 0.025 Social ins. Full sample -0.025-0.051-0.053 Mountain top-dwellers -0.035-0.07-0.061 Mountain base-dwellers -0.025-0.027-0.034 Transferred Full sample -0.008-0.021-0.025 Mountain top-dwellers -0.008-0.018-0.023 Mountain base-dwellers -0.009-0.0270.025 Durables Full sample -0.032-0.0150.00004 Mountain top-dwellers -0.042-0.018-0.001 Mountain base-dwellers -0.024-0.010.0005 Housing Full sample. -0.011-0.003 Mountain top-dwellers. -0.009-0.001 Mountain base-dwellers. -0.014-0.004

15 6. Discussion and Conclusion For the measurement of living standards, services a household enjoy from durable goods and housing, were quantified and found to have decreasing marginal effect on total income equality. Policy implications from marginal effects of different sources of income on total inequality: – More income from off-farm jobs increases income inequality, implied by the positve sign, although in 2008 such effect is negative (mainly contributed by mountain top dwellers). – Good findings: effect of social insurance and transferred income on equality! Implication for relevant policy. – Housing and durables’ marginal effect as expected.

16 Thank you for your attention! yuanyuan.yi@economics.gu.se


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