Share:


Expenditure fluctuation and consumption loss: rural spatial poverty in China

    Xiang Luo Affiliation
    ; Jingjing Qin Affiliation
    ; Qing Wan Affiliation
    ; Gui Jin Affiliation

Abstract

Poverty is a challenge faced by all countries worldwide. This paper focuses on a factor that has been less well documented: the consumption loss of farmer households caused by the fluctuation of rural public expenditure. Based on large-scale micro household data and climate data, the instrumental variable estimation results show that every 1% fluctuation of rural public expenditure will lead to a 0.113% decrease in farm household consumption. In addition, the fluctuation of rural public expenditure is also a main cause of long-term consumption loss of farmer households. Furthermore, it was found that the impact of rural public expenditure fluctuation on consumption loss is of certain spatial heterogeneity. The worse the spatial environment is, the more serious the consumption loss will be. The policy suggestion of this paper is to ensure a stable scale of rural public expenditure through the central transfer payment, so as to improve the ability of local governments to implement counter cyclical public policies, and transform local finance (industrial investment) into public finance (infrastructure and education) to improve the local space environment. Overall, this study reveals the impact of spatial externality on rural poverty from the perspective of public expenditure fluctuation, and at the same time provides empirical evidence for a better evaluation of the relationship between development and poverty and support for rational regional anti-poverty policies.


First published online 08 September 2021

Keyword : expenditure fluctuation, consumption loss, spatial poverty, China

How to Cite
Luo, X., Qin, J., Wan, Q., & Jin, G. (2021). Expenditure fluctuation and consumption loss: rural spatial poverty in China. Technological and Economic Development of Economy, 27(6), 1357-1382. https://doi.org/10.3846/tede.2021.15374
Published in Issue
Nov 18, 2021
Abstract Views
1022
PDF Downloads
614
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Alkire, S., Roche, J. M., Seth, S., & Sumner, A. (2015). Identifying the poorest people and groups: Strategies using the Global Multidimensional Poverty Index. Journal of International Development, 27(3), 362−387. https://doi.org/10.1002/jid.3083

Angelucci, M., Giorgi, G. D., Rangel, M. A., & Rasul, I. (2009). Family networks and school enrolment: Evidence from a randomized social experiment. Journal of Public Economics, 94(3). https://doi.org/10.3386/w14949

Barbier, E. B., & Hochard, J. P. (2019). Poverty-environment traps. Environmental and Resource Economics, 74(3), 1239−1271. https://doi.org/10.1007/s10640-019-00366-3

Bebbington, A. (1999). Capitals and capabilities: a framework for analyzing peasant viability, rural livelihoods and poverty. World Development, 27(12), 2021−2044. https://doi.org/10.1016/S0305-750X(99)00104-7

Besley, T., & Burgess, R. (2003). Halving global poverty. Journal of Economic Perspectives, 17(3), 3−22. https://doi.org/10.1257/089533003769204335

Bird, K., & Shepherd, A. (2003). Livelihoods and chronic poverty in semi—arid Zimbabwe. World Development, 31(3), 591−610. https://doi.org/10.1016/S0305-750X(02)00220-6

Bloom, D. E., Canning, D., & Sevilla, J. (2003). Geography and poverty traps. Journal of Economic Growth, 8(4), 355−378. https://doi.org/10.1023/A:1026294316581

Brückner, M., & Gradstein, M. (2013). Exogenous volatility and the size of government in developing countries. Journal of Development Economics, 105, 254−266. https://doi.org/10.1016/j.jdeveco.2013.08.005

Brückner, M., & Gradstein, M. (2014). Government spending cyclicality: Evidence from transitory and persistent shocks in developing countries. Journal of Development Economics, 111, 107−116. https://doi.org/10.1016/j.jdeveco.2014.08.003

Chiswick, B. R., & Miller, P. W. (1995). The endogeneity between language, earnings: International analyses. Journal of Labor Economics, 13(2), 246−288. https://doi.org/10.1086/298374

Chou, S. Y., Liu, J. T., & Huang, C. J. (2004). Health insurance and savings over the life cycle—a semiparametric smooth coefficient estimation. Journal of Applied Econometrics, 19(3), 295−322. https://doi.org/10.1002/jae.735

Christiaensen, L., & Demery, L. (2007). Down to earth: Agriculture and poverty reduction in Africa. The World Bank, Washington D.C. https://doi.org/10.1596/978-0-8213-6854-1

Combes, J., Renard, M., & Tapsoba, S. J. A. (2019). Provincial public expenditure in China: A tale of pro-cyclicality. Economic Change and Restructuring, 52(1), 19−41. https://doi.org/10.1007/s10644-017-9215-4

Cunguara, B., & Darnhofer, I. (2011). Assessing the impact of improved agricultural technologies on household income in rural Mozambique. Food Policy, 36(3), 378−390. https://doi.org/10.1016/j.foodpol.2011.03.002

Daimon, T. (2001). The spatial dimension of welfare and poverty: Lessons from a regional targeting programme in Indonesia. Asian Economic Journal, 15(4), 345−367. https://doi.org/10.1111/1467-8381.00149

Dao, N. T., & Edenhofer, O. (2018). On the fiscal strategies of escaping poverty-environment traps towards sustainable growth. Journal of Macroeconomics, 55, 253−273. https://doi.org/10.1016/j.jmacro.2017.10.007

De Vreyer, P., Herrera, J., & Mesplé-Somps, S. (2009). Consumption growth and spatial poverty traps: an analysis of the effect of social services and community infrastructures on living standards in rural Peru. In Poverty, inequality, and policy in Latin America (pp. 129−155). MIT Press.

Dercon, S., & Christiaensen, L. (2011). Consumption risk, technology adoption and poverty traps: Evidence from Ethiopia. Journal of Development Economics, 96(2), 159−173. https://doi.org/10.1016/j.jdeveco.2010.08.003

Dercon, S. (2002). Income risk, coping strategies and safety nets. World Bank Research Observer, 17(2), 141−166. https://doi.org/10.1093/wbro/17.2.141

Dinkelman, T., & Schulhofer-Wohl, S. (2015). Migration, congestion externalities, and the evaluation of spatial investments. Journal of Development Economics, 114, 189−202. https://doi.org/10.1016/j.jdeveco.2014.12.009

Dollar, D., & Kraay, A. (2002). Growth is good for the poor. Journal of Economic Growth, 7(3), 195−225. https://doi.org/10.1023/A:1020139631000

Dong, Y., Jin, G., Deng, X. Z., & Wu, F. (2021). Multidimensional measurement of poverty and its spatiotemporal dynamics in China from the perspective of development geography. Journal of Geographical Sciences, 31(1), 130−148. https://doi.org/10.1007/s11442-021-1836-x

Epprecht, M., Müller, D., & Minot, N. (2011). How remote are Vietnam’s ethnic minorities? An analysis of spatial patterns of poverty and inequality. The Annals of Regional Science, 46(2), 349−368. https://doi.org/10.1007/s00168-009-0330-7

Eswaran, M., & Kotwal, A. (1990). Implications of credit constraints for risk behaviour in less developed economies. Oxford Economic Papers, 42(2), 473−482. https://doi.org/10.1093/oxfordjournals.oep.a041958

Glauben, T., Herzfeld, T., Rozelle, S., & Wang, X. (2012). Persistent poverty in rural China: Where, why, and how to escape? World Development, 40(4), 784−795. https://doi.org/10.1016/j.worlddev.2011.09.023

Guo, B., He, D., Zhao, X., Zhang, Z., & Dong, Y. (2020). Analysis on the spatiotemporal patterns and driving mechanisms of China’s agricultural production efficiency from 2000 to 2015. Physics and Chemistry of the Earth, 120, 102909. https://doi.org/10.1016/j.pce.2020.102909

Gustafsson, B., & Wei, Z. (2000). How and why has poverty in china changed? A study based on microdata for 1988 and 1995. China Quarterly, 144(4), 983−1006. https://doi.org/10.1017/S0305741000019263

Hidalgo-Hidalgo, M., & Iturbe-Ormaetxe, I. (2018). Long-run effects of public expenditure on poverty. The Journal of Economic Inequality, 16(1), 1−22. https://doi.org/10.1007/s10888-017-9360-z

Islam, A., & Maitra, P. (2012). Health shocks and consumption smoothing in rural households: Does micro credit have a role to play? Journal of Development Economics, 97(2), 232−243. https://doi.org/10.1016/j.jdeveco.2011.05.003

Jalan, J., & Ravallion, M. (1999). Are the poor less well insured? Evidence on vulnerability to income risk in rural China. Journal of Development Economics, 58(1), 61−81. https://doi.org/10.1016/S0304-3878(98)00103-5

Jalan, J., & Ravallion, M. (2002). Geographic poverty traps? A micro model of consumption growth in rural China. Journal of Applied Econometrics, 17(4), 329−346. https://doi.org/10.1002/jae.645

Jin, G., Deng, X., Zhao, X., Guo, B., & Yang, J. (2018). Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014. Journal of Geographical Sciences, 28(8), 1113−1126. https://doi.org/10.1007/s11442-018-1545-2

Jin, G., Shi, X., He, D., Guo, B., Li, Z., & Shi, X. (2020a). Designing a spatial pattern to rebalance the orientation of development and protection in Wuhan. Journal of Geographical Sciences, 30(4), 569−582. https://doi.org/10.1007/s11442-020-1743-6

Jin, G., Guo, B. S., & Deng, X. Z. (2020b). Is there a decoupling relationship between CO2 emission reduction and poverty alleviation in China? Technological Forecasting & Social Change, 151, 119856. https://doi.org/10.1016/j.techfore.2019.119856

Knight, J., & Yueh, L. (2008). The role of social capital in the labour market in China. Economics of Transition, 16(3), 389−414. https://doi.org/10.1111/j.1468-0351.2008.00329.x

Kraay, A. (2006). When is growth pro-poor? Evidence from a panel of countries. Journal of Development Economics, 80(1), 198−227. https://doi.org/10.1016/j.jdeveco.2005.02.004

Laajaj, R. (2017). Endogenous time horizon and behavioral poverty trap: Theory and evidence from Mozambique. Journal of Development Economics, 127, 187−208. https://doi.org/10.1016/j.jdeveco.2017.01.006

Liu, K. (2016). Insuring against health shocks: health insurance and household choices. Journal of Health Economics, 46, 16−32. https://doi.org/10.1016/j.jhealeco.2016.01.002

Liu, Y., Liu, J., & Zhou, Y. (2017). Spatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies. Journal of Rural Studies, 52, 66−75. https://doi.org/10.1016/j.jrurstud.2017.04.002

Luo, X., Zhang, Z., Lu, X., & Zhang, L. (2019). Topographic heterogeneity, rural labor transfer and cultivated land use: An empirical study of plain and low-hill areas in China. Papers in Regional Science, 8(5), 2157−2178. https://doi.org/10.1111/pirs.12444

Luo, X., Lu, X., Zhang, Z., & Pan, Y. (2020). Regional differences and rural public expenditure cyclicality: evidence from transitory and persistent shocks in China. The Annals of Regional Science, 65, 281–318. https://doi.org/10.1007/s00168-020-00985-5

Munshi, K., & Rosenzweig, M. (2009). Why is mobility in India so low? Social insurance, inequality, and growth (Working Paper No. 14850). National Bureau of Economic Research. https://doi.org/10.3386/w14850

Narayan, D., Patel, R., Schafft, K., Rademacher, A., & Koch-Schulte, S. (2000). Voices of the poor: Can anyone hear us? Oxford University Press. https://doi.org/10.1596/0-1952-1601-6

Ohno, H. (2015). Limited market participation, financial intermediation, and consumption smoothing. International Journal of Economics and Finance, 7(3), 36–44. https://doi.org/10.5539/ijef.v7n3p36

Ravallion, M. (2001). Growth, inequality and poverty: Looking beyond averages. World Development, 29(11), 1803–1815. https://doi.org/10.1016/S0305-750X(01)00072-9

Ravallion, M., & Wodon, Q. (1999). Poor areas, or only poor people? Journal of Regional Science, 39(4), 689–711. https://doi.org/10.1111/0022-4146.00156

Rosenzweig, M., & Binswanger, H. (1993). Wealth, weather risk and the composition and profitability of agricultural investments. Economic Journal, 103(416), 56–78. https://doi.org/10.2307/2234337

Rozelle, S., Zhang, L. X., & Huang, J. K. (2000). China’s war on poverty (Working Paper No. 60). Center for Economic Research on Economic Development and Policy Reform, Stanford Institute for Economic Policy Research, Stanford University.

Segal, B., & Podoshen, J. S. (2013). An examination of materialism, conspicuous consumption and gender differences. International Journal of Consumer Studies, 37(2), 189–198. https://doi.org/10.1111/j.1470-6431.2012.01099.x

Sen, A. (1999). Development as freedom. Oxford University Press.

Schultz, T. P. (2004). School subsidies for the poor: evaluating the Mexican Progresa poverty program. Journal of Development Economics, 74(1), 199–250. https://doi.org/10.1016/j.jdeveco.2003.12.009

Shim, E. Y. (2014). The impact of conditional cash transfer programs under risk-sharing arrangements: Schooling and consumption smoothing in rural Mexico. University of Pennsylvania.

Shujaat, F., & Usman, A. (2020). Economic growth and rural poverty in Pakistan: A panel dataset analysis. The European Journal of Development Research, 32(4), 1128–1150. https://doi.org/10.1057/s41287-020-00259-y

World Bank. (1981). World Development Report 1981/1982. Oxford University Press.

World Bank. (2000a). Geographical targeting for poverty alleviation: Methodology and applications (D. Bigman, & H. Fofack, Eds.). Washington, D. C.

World Bank. (2000b). World Development Report 2000/2001. Oxford University Press.

Xu, L., Zhang, Q., & Zhang, X. (2011). Evaluating agricultural catastrophic risk. China Agricultural Economic Review, 3(4), 451–461. https://doi.org/10.1108/17561371111192310

Zhou, L., & Xiong, L.-Y. (2017). Natural topographic controls on the spatial distribution of povertystricken counties in China. Applied Geography, 90, 282–292. https://doi.org/10.1016/j.apgeog.2017.10.006

Zimmerman, F. J., & Carter, M. R. (2003). Asset smoothing, consumption smoothing, and the reproduction of inequality under risk and subsistence constraints. Journal of Development Economics, 7(2), 233–260. https://doi.org/10.1016/S0304-3878(03)00028-2

Zou, W., & Liu, Y. (2010). Skilled labor, economic transition and income differences: A dynamic approach. Annals of Economics and Finance, 11(2), 247–275.