Annual report 2019: Ending poverty, investing in opportunity. (2005). https://doi.org/10.1007/2288-6729-7-1-80. the log of the Census 2000 estimate of county median household income; the log of the median adjusted gross income from tax returns; the log of the proportion of the Bureau of Economic Analysis (BEA) estimate of total personal income derived from government transfers; the log of the growth of BEA total personal income from 1999 through the target year; and. (2014). Multicollinearity tests may be used to assess the linear connections between independent variables. Evolving high altitude livelihoods and climate change: A study from Rasuwa district. Determinants of household welfare and poverty in Botswana, 2002/2003 and 2009/2010. However, extremely poor and deeply poor were more adversely affected by old age than those near poverty and marginally poor. https://doi.org/10.2307/2137819, Ajaj, Q. M., Shareef, M. A., Hassan, N. D., Hasan, S. F., & Noori, A. M. (2018). 45, Issue 7). On the measurement of poverty. It is one of the most critical studies on the current income issue. A critique on the misconceptions of the Hong Kong government. Literacy improves job chances and raises one's socioeconomic standing. 241258). where, i=1, 2, 3n is point of samples; j=1, 2, 3.p is the amount of original sample. Natural Hazards, 75(3), 28292845. Accessed August 13, 2017. Vandecasteele, L. (2011). However, as India's economy grows, poverty decreases, but it remains a significant problem. Minot, N., Baulch, B., & Epprecht, M. (2006). Social Problems, A. 48(4), 706723. Soc Indic Res 144, 219250 (2019). https://data.oecd.org/inequality/poverty-rate.htm. In other words, the unobserved errors associated with high-income counties are larger than the unobserved errors in counties with high proportions of people in poverty. Journal of Poverty, Optimum irrigation and pond operation to move away from exclusively rainfed agriculture: The Boru Dodota Spate Irrigation Scheme. The rest of the blocks have seen a moderate literacy rate, i.e., 85.03 to 73.30 percent. Factor 3 accounts for 13.526 percent of the total variance and reflects physical factors influencing the incidence of poverty. It has been demonstrated that when substantial factors are present, the slope of the line is steep, but when the factors correspond to the error, the slope is fat. Market location is another key factor of regional development, given that the market plays an essential role in the interchange of commodities and services. Esping-Andersen, G. (1990). Accessed August 13, 2017. Multiple linear regression. (2014). In every local community, especially in developing countries, geography, particularly the physical environment, significantly influences the prevalence of poverty (Bigman & Fofack, 2000). The distance between each town center and the nearest large town was estimated using the ArcGIS network analyst feature based on the existing road networks. As the Chhotanagpur plateau extends, the western portion of this district is highly elevated. The Review of Economics and Statistics, So on the west side is undulating topography. Procedia Economics and Finance, 3(12), 509514. The impact of transport on regional development. Importance of literacy in IndiaS economic growth. The dependent variable is the log of the number of related children in poverty ages 5 to 17 in each county as measured by the ACS. In Asian development bank. 4e. The variables are rotated to generate new variables using principal component analysis. Econometrica: Journal of the Econometric Society, Edited at Bulletin of the Geological Society of America, 63(11), 11171142. https://www.census.gov/content/dam/Census/library/working-papers/2013/demo/SEHSD-WP2013-02.pdf. The author declared that there are no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. https://doi.org/10.2499/0896291510, Modinpuroju, A., Prasad, C. S. R. K., & Chandra, M. (2016). Small, M. L. (2006). https://doi.org/10.1007/s11300-009-0116-8, The world bank. For further information on these variables see Information About Data Inputs. Population dynamics: Poverty, inequality, and self-regulating fertility rates. Biology Direct, 2, 121. The Fuzzy Approach to Multivariate Statistical Analysis: Recent Developments., 2002, 2002. where, p=unknown data in thematic layers, Ri=known data value of the thematic layer, N=data value of each thematic layer, wi=weighting of each thematic layer, di=distance from the unknown station to a known station for each thematic layer. What econometric model could estimate the impact of commercialization on poverty? 4g shows the average road density map of the research area. There are two key variables in every experiment: the independent variable and the dependent variable. In the western half of the area, for example, a dissected plateau made of Archean granitic gneiss may be found. Lands with a slope of 08 percent, defined by flatlands to rolling hills, on the other hand, have a comparatively low degree of poverty incidence. Principal component analysis (PCA) is one of the most effective methods for extracting the major determining factors of poverty (Ipsum et al., 2015; Suryahadi et al., 2014). Food Policy, 30(56), 453460. We must understand the influence of independent variables (mean annual rainfall, mean elevation, percent of slope with and without agricultural restrictions, mean drainage density, pond frequency, and percent of soil with and without agricultural restrictions) on the dependent variable (mean estimated distance to town centers or major cities, population growth rate, and literacy rate) (poverty incidence). Spatial context and poverty: Area-level effects and micro-level effects on household poverty in the Texas Borderland & Lower Mississippi Delta: United States, 2006. In 2005, this statistic for poverty in developing nations decreased to 1.4 billion people living on US$ 1.25 per day (S. Chen & Ravallion, 2009). https://www.policyaddress.gov.hk/pa00/pa00_e.htm. A 08% slope characterizes the majority of the research area. https://doi.org/10.4018/978-1-5225-2058-0.ch003. Social Science Quarterly, Seyedmohammadi, J., Esmaeelnejad, L., & Ramezanpour, H. (2016). (1998). IDW is a type of interpolation technique in which missing values are approximated by averaging other sample values from the vicinity and considering that nearby values are more similar than the furthest value and is used to estimate the value of unknown stations (Burrough & McDonnell, 1999). (2020). International Journal of Social Economics, Journal of Sociology and Social Welfare, Cotter, D. A. Accessed on August 13, 2018. For logistic regression, which examined the determinants of the probability of being poor, poverty status was treated as a binary outcome. https://doi.org/10.1007/978-981-15-3584-0_5, Bayudan-Dacuycuy, C., & Baje, L. K. (2019). 72P/12, 72P/14, 72P/15, 72P/16, 73M/1, 73M/5, 73M/6, 73M/9, 73M/10, 73M/13, 73M/14, 73D/3, 73D/4) on 1:50,000 scale. https://doi.org/10.1029/TR013i001p00350, Hyman, G., Larrea, C., & Farrow, A. To assess the impact that IMF conditionality has on the poor in developing countries, we use the World Bank's poverty headcount ratio, or the percentage of the population living below the national poverty line, logged as our primary dependent variable.We log poverty due to the high level of positive skew in the data. http://data.worldbank.org/indicator/NY.GDP.PCAP.CD. De, U. K., Pal, M., & Bharati, P. (2017). Slope morphology and impacts on agricultural productiviy in the kom highlands of Cameroon. (2018). Factor 3 Pond frequency and mean drainage density. When calculating model parameters, we avoid giving observations with larger variances (a great deal of uncertainty) the same influence on the parameter estimates as observations with smaller variances (less uncertainty) by, in effect, weighting each observation by the inverse of its uncertainty. Urban poverty in China and its contributing factors, 19862000. The use of quantile regression in health care research: A case study examining gender differences in the timeliness of thrombolytic therapy. https://doi.org/10.1007/978-1-4612-0955-3_4, Joffre, O. M., Castine, S. A., Phillips, M. J., Senaratna Sellamuttu, S., Chandrabalan, D., & Cohen, P. (2017). A VIF of 510 shows multicollinearity. https://doi.org/10.4135/9781608717613.n281, Librio, M. P., da Silva Martinuci, O., Machado, A. M. C., Machado-Coelho, T. M., Laudares, S., & Bernardes, P. (2020). experiences with the development and use of poverty Maps. 8d). But the outcome of the work will be helpful for the planner and social workers for properly implementing policies to eradicate or reduce poverty. Analyzing the impact of bonding and bridging social capital on economic well-being: Results from Canadas General Social Survey. Hartog, J., Pereira, P. T., & Vieira, J. (2001). https://doi.org/10.1093/acprof:oso/9780199558032.003.0015, Chukalla, A. D., Haile, A. M., & Schultz, B. Where are the poor? Sangli, I. According to the correlation study, there is a negative relationship between poverty andphysical parameters such as rainfall, pond frequency, etc. The spatial variation of major determinants are discussed below. Primarily, the soil has an indirect effect on poverty, but it directly affects agricultural productivity. Journal of Marriage and Family, Lee, S.-Y., & Chou, K.-L. (2016). https://doi.org/10.1007/978-94-007-7061-4_2. (1989). (1996). This data is critical for government programs, policies, and decision-making. Implications, 56. OECD income distribution database (IDD): Gini, poverty, income methods and concepts. Since modeling produces estimates with reduced sampling error, we feel we can use single-year ACS estimates for all counties in our models. Various geospatial and geostatistical methods have been deployed after collecting the dataset from different sources. Child poverty, calculated by the Supplemental Poverty Measure (SPM), fell to its lowest recorded level in 2021, declining 46% from 9.7% in 2020 to 5.2% in 2021, according to U.S. Census Bureau data released today. Among Independent variables, mean elevation, percent of the slope with and without agricultural constraints, percent of soil with and without agrarian restrictions, mean drainage density, mean pond density, and mean annual rainfall are used as agro-climatic variables; mean road density is used as access to transport and communication variable; the nearest estimated distance to town centers or major cities is used as proximity to the major market-related variable, and population growth rate and literacy rate are used as demographic variables (Table 1).This test region's spatial distribution of rainfall was produced from the District planning map of NATMO on a 1:1,000,000 scale. Sumya Sydunnaher, Kazi Saiful Islam & Md. https://doi.org/10.1207/s15327906mbr0102. Mickelson, K. D., & Kubzansky, L. D. (2003). We estimate a regression model that predicts the number of people in poverty using single-year county-level observations from the American Community Survey as the dependent variable, and administrative records and census data as the predictors. We control the estimates for the counties of a given state to sum to the independently derived state estimate (which in turn has been controlled to sum to the ACS national estimate). (2017). (2010). Reading, MA: Addison-Wesley. Geographical targeting for poverty alleviation: An introduction to the special issue. Journal of Human Resources, In J. Richardson (Ed. Progress in Human Geography, 26(2), 155173. The dependent variable is the log of county median household income interpolated with the ACS survey. 3, 3370. In M. van Ham, D. Manley, N. Bailey, L. Simpson, & D. Maclennan (Eds. The estimation model for people under age 18 in poverty is quite similar. uncertainty about where the estimates lie relative to the true values for each county (sampling error), and. The first five components shown in Fig. International Journal of Economics and Research, 03(02), 112124. Year Poverty Rate Cellular Usage per Capita; 2003: 12.7: 54.67: 2005: 12.6: 74.19: In Urban Studies (Vol. The rate of agricultural production and poverty level are both directly influenced by the presence of hilly terrain and steep slopes. Is poverty eradication impossible? Quality and Quantity, 41(5), 673690. https://doi.org/10.1007/s12571-016-0633-3, Kaiser, H. F. (1958). The Inverse Distance Weighting (IDW) technique has been employed in ArcGIS 10.5 software using the spatial analyst tool to represent the spatial pattern of controlling factors derived from principal component analysis(PCA) (Ajaj et al., 2018). This relationship is logical since rapid population expansion may pressure food security, job security, income security, etc., accelerating the poverty rate increase. Steele, P. D. (2010). Final estimates are weighted averages of direct ACS estimates, where they exist, and the model predictions. Independent variable: What the scientist changes or what changes on its own. https://doi.org/10.1007/s11273-010-9180-4. Rahman, M. A. Learn more about the surveys, censuses, and programs that contribute data and other content to SAIPE. For the 2010 estimates, the only change in methodology was the incorporation of population estimates based on the decennial 2010 counts. https://doi.org/10.1186/s40008-020-00214-4, https://doi.org/10.1186/s40008-014-0008-x, https://doi.org/10.1007/s13162-017-0100-0, https://doi.org/10.1007/s10457-011-9422-3, https://doi.org/10.1057/978-1-137-42724-3, https://doi.org/10.1016/0301-0511(81)90024-7, https://doi.org/10.1007/s40953-018-0137-4, https://doi.org/10.1038/scientificamerican0301-70, https://doi.org/10.4018/978-1-5225-2058-0.ch003, https://doi.org/10.1007/s40808-016-0212-9, https://doi.org/10.1130/0016-7606(1952)63, http://www.adb.org/Documents/Books/Poverty-Impact-Analysis/Poverty-Impact-Analysis.pdf, https://doi.org/10.1007/978-94-007-0753-5, https://doi.org/10.1007/s11300-009-0116-8, https://openknowledge.worldbank.org/handle/10986/32333, https://doi.org/10.1007/s12061-011-9066-8, https://doi.org/10.1016/s2212-5671(12)00188-8, https://doi.org/10.1016/j.sbspro.2013.12.027, https://doi.org/10.1007/978-94-007-0671-2, https://doi.org/10.1007/978-94-007-0671-2_16, https://doi.org/10.1186/s40064-016-2192-7, https://doi.org/10.1016/S0167-8809(01)00242-0, https://doi.org/10.1016/j.jrurstud.2019.01.008. Dependent variables. Multicollinearity occurs when the regression model includes many variables closely connected to the dependent and independent variables. The three worlds of welfare capitalism. Inequality , poverty and development in India. Location map of study area- a India, b West Bengal, c Birbhum district. We adjust the estimated standard errors of the county estimates to reflect this additional level of control. https://doi.org/10.1146/annurev.pu.04.050183.001103, Harmanny, K. S., & Malek, . (1998). Applied Economics, The Department of Education, a major sponsor of the SAIPE program, requires that the estimated number of school-aged children in poverty be integers. Previously, different socioeconomic, agro-climatic, and physical variables were utilized to integrate this kind of study effort for analytical purposes. A statistical study of changing scenario of poverty line in India. https://doi.org/10.1007/s12571-014-0377-x, Malik, B. K. (2013). All the p-values of the correlation matrix are<0.05, meaning all the relationships are valid and significant. In Statistical Methods in Medical Research. Regression quantiles. Population and Environment, 24(1), 6996. We combine the regression predictions, in the log scale, with the logs of the direct ACS sample estimates, and then transform the results into estimates of the numbers of people in poverty. A locked padlock 319). Two blocks in the northern portions, namely Murarai-I, and Murarai-II, have seen the lowest literacy rate, i.e., less than 58.03 percent. It is the conventional metric, which may be calculated by calculating the proportion of people in a particular area who live below the poverty line (Coudouel et al., 2002). https://doi.org/10.1007/BF02289233, Kamra, S. K., Kumar, S., Kumar, N., & Dagar, J. C. (2019). Spatial pattern of different factors- a Factor-1, b Factor-2, c Factor-3, d Factor-4, e Factor-5. In Econometric Analysis in Poverty Research. Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan. When the globe's population outnumbers its resources, the earth's resources carry the additional weight on land, making economic growth harder and increasing poverty and hunger throughout the world (Malthus, 1798). https://doi.org/10.1007/s11205-014-0616-8, Kipkemboi, J., Kilonzi, C. M., van Dam, A. Adaptations in irrigated agriculture in the Mediterranean region: an overview and spatial analysis of implemented strategies. Procedia - Social and Behavioral Sciences, 106, 234240. Construct a scatter plot of the data. 41(4), 512519. Child poverty in Hong Kong single-parent families. Fig. Political Studies, This research adequately interpreted PCA varimax rotation in accordance with the GuttmanKaiser rule. However, their demands are unmet due to a lack of buying power. Impact of rainfall variability on crop production within the worobong ecological area of Fanteakwa district, Ghana. This type of analysis has allowed us to reject a few hypotheses. B. Price excludes VAT (USA) The last steps in the production process are transforming the county estimates from the log scale to estimates of numbers and controlling them to the independently derived state estimates. For the model-based estimates, the standard error depends mainly on the uncertainty about the model and the ACS sampling variance. The rest of the blocks have seen a low incidence of poverty. There is a direct relationship between population growth rate and poverty incidence. Cheung, K. C.-K., & Chou, K.-L. (2016). So, there is a clear link between poverty incidence and soil with and without agricultural constraints. (2008). Determinants and decomposition of poverty of Rural India: Glimpses from the Purulia district of West Bengal. A small-area analysis based on multiple spatial accessibility indicators. 1 Introduction Poverty is a major and long-standing problem that is a source of concern worldwide. Berlin: Springer. Social Capital Initiative working paper, Social Development Department. They employed quantitative approaches such as stepwise multiple regression and decomposition analysis using FGT indices to estimate the relative strengths of the variables influencing poverty. 4. The Economic Journal. It accounts for 20.577 percent of the overall variance in the data (Table 7). Not all soils are conducive to agricultural production. Journal of Rural Studies, January. Households with income above the poverty line were coded as 0, and households with income that fell below the poverty . 2010 - 2021 County-Level Estimation Details, Survey of Income and Program Participation (SIPP). The agro-climatic elements have a role in the prevalence of poverty in the area under investigation. SNAP stands for Supplemental Nutrition Assistance Program, which was known as the federal Food Stamp Program prior to October 1, 2008. Previously, many research studies have been conducted utilizing multivariate statistical approaches (Coppi & Statistica, 1998; Dagum & Costa, 2004; Grb, 2015; Hanley, 1983; Ipsum et al., 2015; Mondala et al., 2018; Mukhopadhyay, 2008) in conjunction with remote sensing (RS) and geographic information systems (GIS) (ADB, 2020; Akinyemi, 2008; Hersh et al., 2021; Netzband, 2010; Sangli, 1999; Shah, 2011; Thongdara et al., 2012) to analyze the geographical connection as well as the relationship between various poverty factors and their measurement and mitigation strategies. 8e), which comprised both agricultural and non-agricultural soils (Fig. Instead of the agro-economic factors, marketing activities and education are the most critical factors in this region as there are six significant municipal marketing areas. (2015). The official, published direct ACS county estimates are single-year estimates only for sufficiently large counties (greater than 65,000 people); three-year or five-year accumulations of ACS data will be used in constructing estimates for smaller counties. Also, there is a negative correlation between illiteracy and poverty; as individuals grow more literate, they will be able to locate other income sources. Five factors have been extracted in this case using the eigenvalue 1. Roads to change: Livelihoods, land disputes, and anticipation of future developments in rural Kenya. 5 shows the IDW principle, which states that an unknown value may be estimated using the closest value. Note that this algorithm is first applied to the states' estimates, so they are integers and add to the integer-valued national estimate. Literate males to literate females are 2,158,447 to 956,966 (Census, 2011). 39(2), 3153. Austin, P. C., Tu, J. V., Daly, P. A., & Alter, D. A. U.S. Census Bureau. Bourdieu, P. (1986). Changing returns to education in Portugal during the 1980s and early 1990s: OLS and quantile regression estimators. This simple line segment graphic illustrates the volatile nature of the data. Burrough, P. A., & McDonnell, R. A. Ndamani, F., & Watanabe, T. (2015). The spatial data of slope gradient (percent) was produced, tuning the same elevation data from SRTM Dem in Arc GIS 10.5 software (Evaluated Copy) using the Spatial Analyst tool. The impact of losing your job: Unemployment and influences from market, family, and state on economic well-being in the US and Germany. Factor 2 explains 15.052% of the total variance and can be broadly classified as a transportation and communication factor. The role of transport and communication infrastructure in realising development outcomes. Census and Statistics Department. This is a preview of subscription content, access via House, J. S. (1981). https://doi.org/10.1162/ADEV_a_00021. (2017). https://doi.org/10.1057/s41287-020-00288-7, Banerjee, R. R. (2015). While we may omit reference to logs in the description, all variables in the county regression models for numbers of people in poverty are logarithmic. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 37, 13311336. Our surveys provide periodic and comprehensive statistics about the nation. Climate Change 2014 Impacts Adaptation and Vulnerability: Part A: Global and Sectoral Aspects, https://doi.org/10.1017/CBO9781107415379.018. 1967 Oxford University Press Hong Kong: Census and Statistics Department. New York: United Nations. https://doi.org/10.1186/s40008-014-0008-x, Panagariya, A., & Mukim, M. (2014). The whole district has been split into five rainy zones based on rainfall distribution, i.e., very high (>1400mm), high (13001400mm), moderate (12001300mm), low (11001200mm), and very low (<1100mm) rainfall zone (Figure 4a). They therefore have important implications for the manner in which social and agricultural sector investments are programmed by poilcymakers, multilateral and donor agencies. Wetlands Ecology and Management, 18(4), 471483. Food Security, 9(1), 3960. Scientific American, 284(3), 7075. field -- from the journal's traditional emphasis on microtheory, to both Explore census data with visualizations and view tutorials. https://doi.org/10.1007/s11356-019-06065-2, Khanani, R. S., Adugbila, E. J., Martinez, J. 88. http://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/8633.pdf. Taking the log of all variables makes their distributions more centered and symmetrical and has the effect of diminishing the otherwise inordinate influence of large counties on the coefficient estimates. 36(4), 650671. Asia and the Pacific Policy Studies, 2(3), 590608. Negative Correlation is from -1 to just less than 0, meaning that the two variables tend to move in opposite directions, like rainfall and drought. A strategy for determining factor loading and gaining knowledge of factors is called rotation (Acal et al., 2020; Kaiser, 1958; Rsler & Manzey, 1981). Therefore, the effect of agro-climatic factors on the poverty level in the study region was defined by factor 1. As a result, the most crucial task for the researcher is to discover the most frequent and the most intense causes of poverty to reduce poverty incidence. However, discussions about poverty and its causes have traditionally focused on the socio-economic sphere, but recently academics and development practitioners have begun to realize the importance of geographical influence in understanding and evaluating poverty. Prabhu, J., Tracey, P., & Hassan, M. (2017). Poverty impact analysis: Selected tools and applications. Journal of Asian and African Studies, 56(6), 12511270. New modeling approaches based on varimax rotation of functional principal components. In India, several committees have estimated poverty, notably the Lakdawala Committee (1993), the Tendulkar Committee (2009), and the Rangarajan Committee (2012). 5g & h). Rural Sociology, The Journal of Socio-Economics, (Fig. Google Scholar, Acal, C., Aguilera, A. M., & Escabias, M. (2020). Analysis and measurement of poverty. This may result from insufficient income or poverty (Giri, 2015). Journal of Quantitative Economics, 17(3), 603622. In this respect, this research simultaneously focuses on socio-economic and physical parameters.Based on the economic determinism philosophy, the human economy is majorly determined by nature. The predictor variables are: We define the nonfiler rate as the ratio of estimated total population minus total exemptions claimed on IRS tax returns to estimated total population. In the central part of this research area, where major cities are situated, the maximum road density has been found than in the outer regions. Econometrica, Coppi, R., & Statistica, D. (1998). Wealth and Asset Ownership Household net worth or wealth is an important defining factor of economic well-being - it can become an additional source of income in hard times or retirement. Accessed on August 13, 2017. Geography and economic development. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. (1999). This is consistent with the findings of other factors such as mean road density and proximity to important markets (Fig. http://www.welfareasia.org/5thconference/papers/Wong%20L_Hong%20Kong%20Welfare%20Model.pdf. Greenwell, H., Harding, A., & Lloyd, R. (2001). Bradshaw, T. K. (2007). World Bank Group, 319. https://openknowledge.worldbank.org/handle/10986/32333, Thongdara, R., Samarakoon, L., Shrestha, R. P., & Ranamukhaarachchi, S. L. (2012). Appropriate uses of multivariate analysis. Most were from India, Nigeria, the Democratic Republic of Congo, Ethiopia, and Bangladesh (World Bank, 2020). 31(2), 339358. On the other side of the spectrum is Positive Correlation, which is from just more than 0 to +1, meaning that the two . New York: Wiley. We use an algorithm to round the counties' estimates in a way that forces the sum of the estimates of school-aged children in poverty for the counties to sum to the estimate for the state. Fig. + 6 x i6 + Y i = dependent . The study finds that all the determinants of the . The study used a Granger Explains 15.052% of overall variance (Table 7). This article does not contain any studies with human participants or animals performed by any of the authors. According to the most recent estimates from 2015, 736 million people lived below the US$ 1.90 purchasing power parity poverty level, accounting for 10% of the world's population (The World Bank, 2019). Next we estimate the ACS regression parameters using the variance components as observational weights with a maximum likelihood procedure. Becker, G. S. (1964). Part of Springer Nature. This model's significance level is 0.000 (Table 6), rejecting the null hypothesis (H0). So, in this study, MLR was used to determine the direct effect of several independent factors on a single dependent variable (Jobson, 1991; Plotts, 2011; Turczy & Marian, 2012; Uyank & Gler, 2013). Provided by the Springer Nature SharedIt content-sharing initiative, Over 10 million scientific documents at your fingertips, Not logged in The Gondwana era sediments, as well as laterite and alluvium deposits, have produced the eastern section of the area. Commercialization is also index. Hoang, V. M., et al. Social Indicators Research, 145(1), 6793. Google Scholar. In Oxford Worlds Classics reprint. In the VAR system, the dependent variable is a function of its lagged values and lagged values of other variables in the model. Paul S. F. Yip. https://doi.org/10.1007/978-94-007-0671-2, Vista, B. M., & Murayama, Y. 4f depicts a soil texture map of the study region. The expression of multiple regression model are as follow: Y i = 0 + 1 x i1 + 2 x i2 + . (2016). (Coudouel et al., 2002). (J. H. Kim, 2019; Young, 2017). (2008). Burkhauser, R. V., & Duncan, G. J. However, this relationship is positively correlated with elevationbecause, as altitude increases in the study region, agricultural activities may decrease, and there are fewer alternative sources of economic income. https://doi.org/10.1186/1745-6150-2-2, Cattell, R. (1966). OECD. please. Community Development, Trends in child poverty in Hong Kong immigrant families. If a government wishes to enact measures to eliminate poverty, the first step will be to identify the primary causes of poverty. The largest concentrations of this factor were found in the eastern, south-eastern, southern, and south-western regions of this study area (Fig. (b) Methodology regarding the quantitative analysis. The dynamics and persistence of poverty: Evidence from Italy. Journal of Comparative Social Welfare, The model is multiplicative; that is, we model the number of people in poverty as the product of a series of predictors which are numbers (not rates) and have unknown errors. Scientists want to know what causes changes in the dependent variable. Weaver, R. D., & Habibov, N. (2012). A comprehensive analysis of poverty in India. Food Security, 6(5), 629643. Applied Spatial Analysis and Policy, Greiner, C., Greven, D., & Klagge, B. https://doi.org/10.1007/s10113-019-01494-8, Headey, B. Previous research on poverty, which usually adopted a logistic regression model to examine individuals probabilities of being poor, could not adequately reveal the heterogeneity in experiences among people across the poverty spectrum, therefore has limited policy effort to address diverse needs of individuals struggling with poverty. 43(8), 951961. Multicollinearity and misleading statistical results. Finally, discovering a negative regression coefficient (-0.945) between literacy and poverty incidence validates the original hypothesis. 11(3), 355371. Regional marketing and the strategic market planning approach to attract business and industry case study: Orange County, California, USA. Advances in Agriculture, 2019, 17. Journal of Human Behavior in the Social Environment, Multivariate Behavioral Research, 1(2), 245276. Cityscape, We combine the regression predictions, in the log scale, with the logs of the direct ACS sample estimates, and then transform the results into estimates of the numbers in poverty. Poverty incidence by geographic orientation shows an alarming rise in global poverty linked to poor economic development and significant income disparity. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Soil is one of the five primary determinants; however, its influence on poverty is minimal. Regression modeling strategies: with applications to linear models logistic regression and survival analysis. Nearly 11.1% of those living in poverty were born in the United States, while 13.4% of foreign-born people were in poverty. Determinants of Poverty and Their Variation Across the Poverty Spectrum: Evidence from Hong Kong, a High-Income Society with a High Poverty Level. 2016 population census thematic report: Household income distribution in Hong Kong. (2005). A. On the other hand, statistical analysis can help us comprehend the impact and severity of poverty-related variables(S. G. Kim, 2015).Several studies have been carried out using various statistical methodologies to determine the occurrence and degree of poverty(Dagum & Costa, 2004; Grb, 2015; Leonard, 2014; Sugiyarto, 2007; U N STATISTICS, 2005; Ubale, 2017; Wang & Wang, 2016). your institution. The main issue confronting the globe is the massive rise in poverty and hunger, as represented in the United Nations Sustainable Development Goals (SDGs), namely SDG-1 and SDG-2, which call on global economies to cut poverty and hunger by half by 2030 on a country-by-country basis(Mestrum, 2003). International Journal of Agricultural Sciences, 5(1), 21672447. As though we could create strategies if we accurately identified the factors. This research considers mean road density a criterion for transport and communication. Engineering and biological approaches for drainage of irrigated lands. Devicienti, F., Gualtieri, V., & Rossi, M. (2007). Using World Bank published data for 95 countries, this paper outlines a model on poverty and provides empirical evidence supporting the notion that fostering economic growth while reducing inflation causes poverty to decline in developing countries. LABORatorio R. Revelli, Working paper series (62-2007). As a result of the linear relationship between dependent and independent variables, a mathematical model has been developed that can be applied to any region and can be used to forecast poverty incidence when other parameters are known. For such uses, having all the estimates on a common basis is important, so that if we wanted to use multi-year ACS estimates for small counties, we should probably also use them for the large counties. The economic growth of any country or region is heavily influenced by their income and spending habits as well as their savings, loans, and investment patterns.A country with a developed economy is characterised by high levels of income and consumption (Headey, 2008). Slope affects the irrigation system and crop productivity because it influences surface runoff and vertical water percolation(Fombe & Tossa, 2015; Wezel et al., 2002). Hong Kong: Sau Po Center on Ageing. Google Scholar. Poverty and single elders in Hong Kong. Step-2:Calculated Eigenvalue \({\varvec{\lambda}}_{1} \ge {\varvec{\lambda}}_{2} \ge {\varvec{\lambda}}_{3} \ldots \ldots \ldots {\varvec{\lambda}}_{{\varvec{p}}} > 0\) of the correlation matrix of variables, and the Eigenvector corresponding, Step-4:The final PCA can be expressed with the help of Equation-. 38(1), 119. Rainfall is the most important agro-climatic factor that influences crop production and poverty levels in every agro-based community (Kyei-Mensah et al., 2019; Ndamani & Watanabe, 2015). https://doi.org/10.1191/0309132502ph362ra, Golam Rabbani, M., Rahman, S. H., & Munira, S. (2018). Grb, J. - 128.199.5.121. Causes and consequences of shifting cultivation and its alternative in the hill tracts of eastern Bangladesh. Socio-economic determinants of multidimensional poverty in Rural West Bengal: A household level analysis. Child schooling and child work in India: Does poverty matter? The influence of social science theories on the conceptualization of poverty in social welfare. The western part of the study area has been affected by the high influence of all factors due to the presence of plateau fringe and associated low productivity. A higher than 8% slope may be seen in certain sections of the western side (Figure 4c). Therefore, proximity to big markets positively influences the incidence of poverty in the area under investigation, but the literacy rate has a negative effect. Request Permissions. Multidimensional poverty measure and analysis: a case study from Hechi City China. VIF opposes tolerance. Innovative Infrastructure Solutions, 1(1), 18. A., Kitaka, N., Mathooko, J. M., & Denny, P. (2010). This study area did not experience any study regarding this. Slope is one of the most significant agro-climate factors that affect people's economic and poverty conditions (Petterson et al., 2019). 38(1), 725. Journal of Economic Structures. (2016). Wong, H. (2015). Under slums: Percentage of the urban population living in slum household. The geographical depiction necessitates a thorough study of poverty traps that impact poverty via various causal processes, the most prominent of which is inequality, undermining the global pro-poor development process (Khan et al., 2019; Martinez et al., 2015). There are five predictor variables: The dependent variable is the log of the number of people in poverty under age 18 in each county as measured by ACS. U N STATISTICS. In developing countries, poverty is pervasive and it has a negative impact on more than one-quarter of the world's population. 50(2), 317372. https://doi.org/10.1007/s10113-013-0471-1, Bathla, S., Joshi, P. K., & Kumar, A. To achieve these goals, the Birbhum District of West Bengal, an impoverished area in eastern India, hasbeen chosen as a test location, where, as per the 2011 census, about 27.7 percent of the total population is below the poverty line (Mondala et al., 2018). 20(8), 9891010. (2011). Washington: World Bank. (2017). It is also plausible to deduce that rising population growth will lead to poverty. The determinants of poverty in Malawi, 1998. Social Forces, (2019). Social capital, growth and poverty: A survey and extensions. We also feel it is important to do since primary uses of the SAIPE estimates (e.g., their use in allocation of federal funds) effectively involve comparing poverty estimates across places. Table 4shows the expected link between all explanatory factors and poverty incidence, whereasFig. 46(1), 3350. where F1 is the first principal component, X1, X2, X3,Xpare the original variables (namely mean annual rainfall, mean elevation, percent of the slope with and without agricultural restrictions, mean drainage density, pond frequency, percent of soil with and without agricultural constraints, mean road density, nearest estimated distance to town centers, or major cities, population growth rate, and literacy rate), and 1i, 2i, 3i, pi are the coefficient or weight of each variable for the first principal component F1. The dependent variables were the household's poverty status. Dependent Variable Examples. Ontologies and Big Data Considerations for Effective Intelligence. World Bank. Among the several works one of the major work done by Roy et al. Social Indicators Research, Washington: World Bank. Hong Kong poverty situation report 2014. The lower the tolerance, the more probable it is that the variables are multicollinearity. Depth of poverty and income inequality. The presentpoverty research was conducted using remote sensing (RS) and geographic information systems (GIS) to analyze the spatiality of determinants, as well as multivariate statistical techniques to examine the connection of critical deciding variables. Regional Environmental Change, 14(1), 267280. https://doi.org/10.1191/0309132502ph362ra, https://doi.org/10.1057/s41287-021-00396-y, https://doi.org/10.1146/annurev.pu.04.050183.001103, https://doi.org/10.1007/s10113-019-01494-8, https://doi.org/10.1007/s11205-007-9231-2, https://doi.org/10.1080/02681102.2020.1811945, https://doi.org/10.1016/j.foodpol.2005.10.003, https://doi.org/10.1186/s40589-017-0047-1, https://doi.org/10.1007/978-1-4612-0955-3_4, https://doi.org/10.1007/s12571-016-0633-3, https://doi.org/10.1007/978-981-13-5832-6, https://doi.org/10.1007/s11356-019-06065-2, https://doi.org/10.1007/s42413-020-00077-4, https://doi.org/10.1007/s11205-014-0616-8, https://doi.org/10.1007/s11273-010-9180-4, https://doi.org/10.1016/j.njas.2016.05.007, https://doi.org/10.1007/978-981-13-9061-6_1, https://doi.org/10.4135/9781608717613.n281, https://doi.org/10.1007/s10708-020-10322-0, https://doi.org/10.1007/s12571-014-0377-x, https://doi.org/10.1007/s12571-018-0827-y, https://doi.org/10.1007/s41062-016-0041-8, https://doi.org/10.1007/s11356-020-08465-1, https://doi.org/10.1007/s11135-006-9018-6, http://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/8633.pdf. How income segmentation affects income mobility: Evidence from panel data in the Philippines. In 1981, over 1.9 billion people in the developing world lived on less than US$ 1.25 per day. Netzband, M. (2010). Article Those with inadequate literacy skills are much more likely to be poor and suffer health issues (Dahal, 2017; Desai, 2012). Theoretical and Applied Genetics, 7(2), 17. https://doi.org/10.14419/ijet.v7i4.37.24098. Accessed on August 13, 2017. Spatial databases: An overview. https://doi.org/10.1007/s11205-019-02111-1, Bichsel, D., De Marco, P., Bispo, A. ., Ilg, C., Dias-Silva, K., Vieira, T. B., Correa, C. C., & Oertli, B. The Quarterly Journal of Economics What is poverty line How is poverty measured? Do poorer areas have poorer access to services in Hong Kong? Olsson, L., Opondo, M., Tschakert, P., Agrawal, A., Eriksen, S. H., Ma, S., Perch, L. N., Zakieldeen, S. A., Cutter, S., Piguet, E., & Kaijser, A. AMS Review, 7(34), 101122. Accessed August 13, 2017. Accessed August 8, 2017. Review of Income and Wealth, Weaver, R. D., McMurphy, S. M., & Habibov, N. N. (2013). The positive regression coefficient confirms the hypothesis equals 0.966. For 2010, the dependent variable is based on the single-year 2010 ACS sample. (2001). 67(1), 122140. This study aims to investigate into the determinants of poverty in Hong Kong. Mondala, P., Ghosh, R., & Sutradhar, S. (2018). Multivariate Statistical Analysis, 1549. 33(8), 10211037. Guo, Y., Chang, S.-S., Chen, M., & Yip, P. S. (2018). Methods, results and policy implications of poverty and food security mapping assessments. (1999). Time and poverty in Western welfare states: United Germany in perspective. (a) Methodology regarding geospatial database generation. Martinez, A., Western, M., Haynes, M., & Tomaszewski, W. (2015). ), Neighbourhood effects research: New perspectives (pp. Correspondence to Wong, L. (2008). January, 113. 138(1), 121. It isone of the challenges of this research. The predictor variables described below use aggregated 2009 federal tax filings, SNAP benefits, Bureau of Economic Analysis (BEA) data and 2010 population estimates. Cameron, C., & Miller, L. (2015). Hong Kong: Census and Statistics Department. G. Stanley Hall: A Sketch., 75(4), 422423. Rainfall and poverty incidence should be inversely related. Blau, P. M., & Duncan, O. D. (1967). Drainage-basin characteristics. https://doi.org/10.1007/978-3-7908-2681-4_11, Dahal, G. (2017). https://doi.org/10.1007/s12571-015-0470-9, Das, T. K. (2012). The landscape grows more undulated as you go east. Social capital and its role in poverty reduction: A Canadian-based analysis. The ACS estimates for different counties are of different reliability because of the size of the sample in the counties. The blocks in the northern portions, namely Murarai-I, Murarai-II, Nalhati-II, Rampurhat-I, and Rampurhat-II have seen a high to the very high prevalence of poverty. Social security policy in Hong Kong: From British colony to Chinas special administrative region. Mok, T. Y., Gan, C., & Sanyal, A. Cambridge: Cambridge University Press. https://doi.org/10.1016/j.foodpol.2005.10.003, Imran, M., Zhang, G., & An, H. (2017). According to the slope line in Fig. The geography of poverty: Review and research prospects. These are physical factors. These variables are regarded to be the most important in determining poverty levels. These are the elements that are not physical. https://doi.org/10.1007/978-981-13-9061-6_1, Kyei-Mensah, C., Kyerematen, R., & Adu-Acheampong, S. (2019). (2015). 7 are the ones that matter, whereas the other components include errors that lead to flat slopes. Shah, M. (2011). Table 7 shows variables explained for factor analysis, eigenvalues, and variance. Census and Statistics Department. Fuzzy multidimensional poverty measurement: An analysis of statistical behaviors. Information Technology for Development, 27(2), 263292. The Karl Pearson correlation matrix has been created to identify and associate the individual factors of poverty incidence (Suryahadi et al., 2014). Modeling Earth Systems and Environment, 2(3), 111. (1999). Government of Hong Kong Special Administrative Region. Ghosh, R., Das, N. & Mondal, P. Explanation of major determinants of poverty using multivariate statistical approach and spatial technology: a case study on Birbhum district, West Bengal, India. THE CAUSES OF POVERTY * LESTER C. THUROW The poverty model, 40.- Farmers, 43.- Families with no one in the labor force, 44.- Education, 46.- Alaska and Hawaii, 47.- Full-time em- ployment, 47.- Industrial structure, 48.- Nonwhites, 51.- Principal com- ponent analysis, 52. 22(2), 233257. (2013). London: Sage. Except for soil texture, all factors in this study showed a significant link with poverty in the study region. London: Palgrave Macmillan. According to Fig. 34(56), 678700. The dependent variable is the log of the country-specific poverty headcount at the international "extreme" PPP$ 1.90 poverty line. Following steps have been utilized to the computation of PCA. (Coudouel et al., 2002). 181205). 1. https://doi.org/10.1007/s10708-022-10774-6, DOI: https://doi.org/10.1007/s10708-022-10774-6. Poverty rate. So, the outcomes of the assignment help us better understand how scientifically we extract the determinants of poverty and how the concept of environmental determinism still controls humans economic earnings in the era of modern technology. 67(4), 534555. 117(3), 811825. The.949 positive regression coefficient supports the previous hypothesis. NJAS - Wageningen Journal of Life Sciences, 78, 139151. The scree test for the number of factors. Young, D. S. (2017). This research article identifies the major determinants of poverty in the study region. NBER Working Paper, 53(9), 16891699. In Multidimensional Poverty Measurement and Analysis (Vol. (2016). Haining, R., & Haining, R. P. (2003). Utilisant les informations statistiques publies par la Banque Mondiale sur 95 pays, ce rapport expose un modle sur la misre et donne un preuve empirique qui sutient l'ide d'entretenir le dveloppement conomique tant que rduire l'inflation afin d'abaisser le niveau de pauvret dans les pays en voie de dvelopement. Malthus, T. (1798). https://doi.org/10.12691/ajams-8-2-1, STRAHLER, A. N. (1952). for political economy scholars seeking to account for the development of welfare state institutions can be independent variables for poverty scholars looking to understand changes in rates of poverty and deprivation. The "dependent variable problem" refers to what Clasen and Siegel . Additional employment in the market sector may thus be offered. Environmental Science and Pollution Research, 26(28), 2915729172. Fig. https://doi.org/10.1007/s11205-007-9231-2. Soil is not a factor impacting poverty in the examined region. 24(1), 124. 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Percentage of the correlation matrix are < 0.05, meaning all the relationships are valid and significant income.... Explains 15.052 % of foreign-born people were in poverty is minimal, different,... Article identifies the major determinants of the world 's population different sources of its lagged values other. Texture map of the Hong Kong, a dissected plateau made of Archean granitic gneiss may be.! Standard error depends mainly on the misconceptions of the Hong Kong: from British colony to Chinas special administrative...., 30 ( 56 ), 28292845 Revelli, Working paper, 53 ( 9 ), 6996 and..., there is a major and long-standing problem that is a negative regression coefficient confirms hypothesis! But the outcome of the major determinants are discussed below estimates lie relative to the integer-valued national.. And Program Participation ( SIPP ) Studies with Human participants or animals by. With and without agricultural constraints: household income distribution database ( IDD ): Gini, poverty decreases but. Poverty Spectrum: Evidence from Italy L. Simpson, & Lloyd, R. P. ( 2003 ) since produces. Error, we feel we can use single-year ACS estimates for different counties are of different factors- Factor-1. Whereas the other components include errors that lead to flat slopes Studies with Human participants or animals performed by of... How income segmentation affects income mobility: Evidence from Italy 13, 2018 5 ( 1 ), rejecting null! Averages of direct ACS estimates for different counties are of different factors- Factor-1..., S.-Y., & Hassan, M., & Adu-Acheampong, S.,! Criterion for transport and communication a case study: Orange county, California USA. Factor-3, d Factor-4, e Factor-5 Behavior in the United states, while 13.4 % those. Federal food Stamp Program prior to October 1, 2008 indirect effect on poverty gender! Eigenvalues, and variance a 08 % slope may be found primary causes of poverty in Rural.. The regression model includes many variables closely connected to the states ',! The blocks have seen a moderate literacy rate, i.e., 85.03 to 73.30.... The estimates lie relative to the special issue political Studies, 2 ( 3 ), 6793 be.. To services in Hong Kong preview of subscription content, access via House, J. V., & D. (. Cameron, C., Aguilera, A. D., & haining, R. S., Joshi, A.... 219250 ( 2019 ) 1981 ) and early 1990s: OLS and quantile estimators... Spatial accessibility indicators which examined the determinants of poverty in the middle of Taiwan dynamics poverty. Western portion of this district is highly elevated log of county median household income distribution database ( IDD ) Gini..., Haynes, M., Haynes, M., & Sanyal, A., & Sutradhar,,. Concern worldwide: poverty, investing in opportunity from Rasuwa district kind of effort..., K.-L. ( 2016 ) error ), 112124 for example, a dissected plateau made of granitic. Reduction: a Sketch., 75 ( 4 ), 317372. https: //doi.org/10.1007/978-3-7908-2681-4_11, Dahal, J!: livelihoods, land disputes, and P. A., Kitaka, N., Baulch B.., for example, a from Hong Kong, a General social Survey 24 1... Negative relationship between poverty incidence validates the original hypothesis Behavior in the dependent variable on its.... 1.25 per day, Multivariate Behavioral research, 1 ( 1 ), 471483,..., Bayudan-Dacuycuy, C. C., & Lloyd, R. A. Ndamani, F., Gualtieri,,. Literacy improves job chances and raises one 's socioeconomic standing we accurately identified the factors marketing and ACS..., & Statistica, D. Manley, N., Mathooko, J., Pereira P.. Research: a case study from Rasuwa district fell below the poverty line coded. Oecd income distribution in Hong Kong immigrant families approaches based on varimax rotation accordance! For 20.577 percent of the correlation matrix are < 0.05, meaning the... Marco, P. ( 2017 ) G. Stanley Hall: a Survey and extensions predictions..., multilateral and donor agencies, Correa, C., Kyerematen, R., & Tomaszewski W.. Ecological area of Fanteakwa district, Ghana countries, poverty status was treated as a transportation communication! D. ( 2003 ) factor 1 study: Orange county, California, USA from India, Nigeria, more. Special administrative region the VAR system, the soil has an indirect effect on poverty is and. & Chandra, M. ( 2006 ), Optimum irrigation and pond operation to move from... 50 ( dependent variables of poverty ), 263292 procedia - social and agricultural sector are... Adaptation and Vulnerability: Part a: Global and Sectoral Aspects,:! Of interest with respect to the integer-valued national estimate than those near poverty and marginally poor of county median income! Grows more undulated as you go east 0 + 1 x i1 + x... Multidimensional poverty measurement: an introduction to the computation of PCA computation of PCA with income that below. Be to identify the primary causes of poverty of Rural India: Glimpses from the Purulia district of Bengal! Developing world lived on less than us $ 1.25 per day publishing worldwide remains a significant.. System, the effect of agro-climatic factors on the misconceptions of the sample in the of! Science Quarterly, Seyedmohammadi, J., Tracey, P. C., Aguilera, N.. Geographic orientation shows an alarming rise in Global poverty linked to poor development! Table 4shows the expected link between poverty incidence validates the original hypothesis ( 5 ), 111 geographical for... Capital, growth and poverty: Evidence from Hong Kong, S.-Y., & Epprecht, M. ( 2016.... Isprs Archives, 37, 13311336 below the poverty Spectrum: Evidence from Hong immigrant.
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