poverty and social exclusion in india world bank pdf

Poverty And Social Exclusion In India World Bank Pdf

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Metrics details. Financial inclusion is a key element of social inclusion, particularly useful in combating poverty and income inequality by opening blocked advancement opportunities for disadvantaged segments of the population. This study intends to investigate the impact of financial inclusion on reducing poverty and income inequality, and the determinants and conditional effects thereof in developing countries. The analysis is carried out using an unbalanced annual panel data for the period of — For this purpose, we construct a novel index of financial inclusion using a broad set of financial sector outreach indicators, finding that per capita income, ratio of internet users, age dependency ratio, inflation, and income inequality significantly influence the level of financial inclusion in developing countries.

Furthermore, the results provide robust evidence that financial inclusion significantly reduces poverty rates and income inequality in developing countries. Financial inclusion connotes all initiatives that make formal financial services accessible and affordable, primarily to low-income people. In recent years, financial inclusion has been perceived as a dynamic tool for attaining multidimensional macroeconomic stability, sustainable and inclusive economic growth, employment generation, poverty reduction, and income equality for advanced and developing countries Footnote 1 alike.

These are generally underprivileged population segments, vulnerable groups such as rural dwellers, women, and low-income families who benefit enormously from basic financial services like savings, borrowings, payment, and insurance World Bank Due to insufficient income levels and market discrimination in developing regions, there are still millions of people involuntarily excluded from the financial system, which creates potential loss of savings, investable funds, and accumulation of wealth.

Financial inclusion helps to fill these gaps and provide households and firms greater access to resources needed for finance consumption and investment and thereby raise the level of economic activity. Progress in reducing extreme poverty seems uneven in these regions because of geographical and country-specific factors.

Asia contains Poverty reduction in developing regions is slowing because of the prevailing nature of extreme income inequality, which is considered a powerful threat to economic progress. Therefore, financial inclusion has moved up the global reform agenda and gained great interest for its potential to break the vicious cycle of poverty and lower income inequality.

Real-world financial systems are far from inclusive, so more emphasis is being placed on financial inclusion, which reflects its potentially transformative power to accelerate inclusive development. Given its multifaceted implications, financial inclusion represents a core topic for the World Bank The United Nations member countries have included financial inclusion as a formal target and a key objective in their development agenda Sahay et al. Despite progress in this direction, evidence on the macroeconomic effects of financial inclusion is limited due to inconsistent macro-level data across countries.

Many studies have investigated the determinants of financial inclusion, appropriate measures of financial inclusion at the individual and country level, and effective types of financial services on the user level. However, these studies are not enough to understand the broader macroeconomic implications of financial inclusion. This study seeks to take another step in the existing literature by examining the relationship between financial inclusion, poverty, and income inequality, sampling entire developing countries, focusing on Asia, Africa, and Latin America and the Caribbean region, whose level of voluntary as well as involuntary financial exclusion is relatively higher than that of other countries.

Thus, this study addresses the following questions: first, what are the crucial factors that affect the level of financial inclusion in developing countries? Second, does financial inclusion reduce poverty and income inequality in developing countries? Third, are there any conditions under which financial inclusion can play a more effective role in reducing poverty and income inequality in developing countries?

This study contributes to the following existent financial inclusion related literature. Second, it identifies the determinants of financial inclusion and analyzes the impact of financial inclusion on reducing poverty and income inequality, focusing on entire developing countries in Asia, Africa, and Latin America and the Caribbean region.

Third, it assesses conditional relationships between financial inclusion and other micro- or macroeconomic factors under which financial inclusion mitigates poverty and income inequality in developing countries.

To our knowledge, there are no empirical studies that broadly examine the indirect provisions through which financial inclusion reduces poverty and income inequality. Fourth, it analyzes all major relationships between variables using a panel data set and fixed effect model to properly process endogeneity associated with financial inclusion. This study finds that per capita real GDP and ratio of internet users positively influence the level of financial inclusion in developing countries, while age dependency ratio, inflation, and income inequality have a detrimental effect.

Our results show robust evidence that economies with higher financial inclusion significantly reduce poverty rates and income inequality in developing countries.

Moreover, the interaction terms of financial inclusion with GDP growth and secondary school enrollment ratio are statistically significant for poverty, whereas the interaction terms of financial inclusion with GDP growth and rule of law are statistically significant for income inequality. This suggests that the effectiveness of financial inclusion depends not only on itself, but also on other conditions in reducing poverty and income inequality. The remainder of the paper is organized as follows.

Chapter 2 reviews existing literature related to the topic. Chapter 3 reveals the empirical methodology, data measurement, and construction of the composite financial inclusion index for testing impacts through regression analysis.

Chapter 4 presents the empirical results and discussions, and Chapter 5 concludes with a summary of our findings and policy implications. The concept of financial inclusion has been explained in diverse ways in the existing literature, but all seem to have analogous information content in terms of conclusions.

The World Bank has defined financial inclusion as the share of households and firms who use financial services. Sahay et al. Although there is consensus on the concept of financial inclusion, existing literature lacks a standard method by which financial inclusion can be measured across economies.

Honohan , constructed a financial access indicator by combining bank and MFI account numbers from household survey cross-sectional data in a limited number of countries. They normalized each variable, statistically identified for each dimension using factor analysis, assigned weights to variables and sub-indices, and then aggregated the data through weighted geometric average.

Sarma proposed a multidimensional index of financial inclusion by combining accessibility, availability, and usage dimension, which satisfies some vital mathematical properties and is comparable across countries and over time.

He computed a dimension index for each dimension, aggregated each index based on normalized Euclidian distance of achievement points from a worst and an ideal situation, and then took a simple average. Sarma and Pais , examined country-specific factors associated with the level of financial inclusion by using a classical OLS method for the sample year of Among possible variables, income measured by per capita GDP, adult literacy, rural population, income inequality, physical connectivity indicated by road network, electronic connectivity indicated by phone subscriptions, information availability indicated by internet usage, bank soundness measured by non-performing assets and capital asset ratio, and foreign ownership in the banking sector were significantly associated with the level of financial inclusion.

Evans and Adeoye evaluated the determinants of financial inclusion in Africa by using a dynamic panel data approach for 15 countries over the period of — Allen et al. Only a few studies have investigated the link between financial inclusion, poverty, and income inequality, with mixed results. Park and Mercado tested the factors influencing financial inclusion and the significance of financial inclusion in reducing poverty and lowering income inequality, focusing on 37 developing Asian economies.

They found that per capita income, rule of law, and demographic structure increased financial inclusion, while a higher age-dependency ratio significantly reduced financial inclusion. Primary education completion and literacy rates have no significant effect on the level of financial inclusion in developing Asia. Moreover, financial inclusion significantly reduces poverty; there is also evidence that it lowers income inequality when more regressors are considered.

In the latest version of their paper, Park and Mercado assessed the cross-country impact of financial inclusion on poverty and income inequality across country income groups by introducing a new financial inclusion index for economies, using principal component analysis and a cross-sectional approach. The results indicate that higher financial inclusion significantly co-varies with higher economic growth and lower poverty rates, but only for high and middle-high-income economies, not those that are middle-low and low-income.

However, they did not find significant effect of financial inclusion on income inequality in any income group. Honohan , examined the fraction of the adult population using formal financial intermediaries for economies and its relationship with poverty and inequality.

The composite financial access indicator was constructed by using a cross-sectional series that combined both household survey data sets and published data. The results show that financial access significantly reduced poverty on its own, but not when other control variables were included as regressors, such as per capita income, private credit as a percentage of GDP, inflation, institutions KKZ index , institutions freedom house bank , population size, and a sub-Saharan Africa dummy.

Furthermore, there was evidence that financial access significantly reduced income inequality on its own and also when financial depth measure private credit as a percentage of GDP and inflation was included, but the result did not hold when per capita income and a sub-Saharan Africa dummy were included.

Jabir et al. Taking cross-sectional data of , they found that financial inclusion significantly reduced the level of poverty in sub-Saharan Africa through providing net wealth and larger welfare benefits to the poor.

Burgess and Pande revealed that state-led bank branch expansions into rural unbanked locations significantly reduced rural poverty in India through access to formal sector credit provision and saving opportunities. Brune et al. They found that financial inclusion contributed to reducing income inequality when the regression was controlled for key relevant factors, especially economic development and fiscal policy. Interestingly, financial deepening size of the financial system did not appreciably contribute to a more equal income distribution.

Dabla-Norris et al. The results indicated that higher financial inclusion would initially lead to greater income inequality, but later reduce inequality significantly as financial inclusion continued to grow within Mexican municipalities. Although all of these studies suggest links between financial inclusion, poverty, and income inequality, they lack a comprehensive understanding of their relationship due to their lack of panel data study and a limited set of variables for constructing a financial inclusion index.

This study tries to expand on existing literature regarding impact analysis of financial inclusion on poverty and income inequality with a broad set of variables for financial inclusion index, and a panel data set consisting of a large number of developing countries in Asia, Africa, and Latin America and the Caribbean.

Based on previous studies, this chapter specifies an econometric model to analyze crucial factors that influence the level of financial inclusion, impact of financial inclusion on reducing poverty and income inequality, and conditional relationships of financial inclusion in reducing poverty and income inequality in developing countries. We then describe key measurements issues and compilation of data from different sources. Moreover, we explain the derivation of the three dimensions of financial inclusion by incorporating proxy variables and the construction of a composite financial inclusion index for using that index in different regression models.

This study follows a dynamic panel regression framework and uses a fixed effect estimation method for empirical analysis. For the econometric analysis, this study uses a one-way error component fixed effect model and robust standard errors to address heteroskedasticity.

The explanatory variables in different regression equations mostly follow previous studies by Honohan , , Sarma and Pais , , Allen et al. For determining the crucial factors that influence the level of financial inclusion in developing countries, the following regression equation is specified:.

Here, per capita income, rule of law, population size, secondary school enrollment ratio, and ratio of internet users are expected to be positively associated with financial inclusion, whereas age dependency ratio, inflation rate, and income inequality are expected to have a negative relationship with financial inclusion.

In order to analyze the relationship between financial inclusion and poverty in developing countries, the following regression equation is employed:. Here, financial inclusion is expected to be negatively associated with poverty rates because higher access to financial services by lower-income people generally helps to reduce poverty by facilitating consumption and engaging in economically productive activities.

To analyze the relationship between financial inclusion and income inequality in developing countries, the following regression equation is employed:. Here, financial inclusion is expected to be negatively associated with income inequality because higher access to financial services by lower- and irregular-income people allows them to save and build assets for the future, which helps to reduce unequal income distribution.

For analyzing the conditional effects of financial inclusion on poverty in developing countries, the following regression equation is used:.

The other specifications are similar to the above equations. To analyze the conditional effects of financial inclusion on income inequality in developing countries, the following regression equation is used:. By excluding developed countries, developing countries are taken in total from three regions: 36 countries from Asia, 53 countries from Africa, and 27 countries from Latin America and the Caribbean Appendix A.

Most of the variables are chosen from empirical literature, with some additional variables and modifications. Due to excessive fluctuations of the data among economies, almost all of the variables except for financial inclusion index, GDP growth rate, and rule of law are expressed in logarithm scale in order to improve the robustness of empirical analysis. A detailed description of variables and their sources is presented in Appendix B.

Such a comprehensive measure of financial inclusion is needed to check the extent of financial inclusion across economies, standardize the measure for a large number of developing economies, monitor progress in reaching national financial inclusion targets, and make cross-country comparisons.

This study considers a variety of financial sector outreach indicators under three basic dimensions of an inclusive financial system such as penetration, availability, and usage of financial services, with relevant and consistent macro-level data for a large number of developing economies. Footnote 2 All of the data for computing each dimension are a panel spanning the period of — This reflects the maximum number of users entered into the formal financial system.

Then a weighted average of these two indices is considered, using 0. As deposit accounts index is an imperative indicator to identify the size of the banked population and a measure of more consolidated stages of financial system, we assign a weighted average of 0.

Furthermore, the depositor index gets less weight of 0. Finally, as penetration in the financial system is the primary measure of financial inclusion and data in determining whether an individual has penetrated in the financial system are also available, we assign an overall weight of 1 to the penetration dimension for calculating CFII.

Poverty and Social Exclusion in India

This site uses cookies to optimize functionality and give you the best possible experience. If you continue to navigate this website beyond this page, cookies will be placed on your browser. In every country, some groups confront barriers that prevent them from fully participating in political, economic, and social life. These groups may be excluded not only through legal systems, land and labor markets, but also discriminatory or stigmatizing attitudes, beliefs, or perceptions. Disadvantage is often based on social identity, which may be derived from gender, age, location, occupation, race, ethnicity, religion, citizenship status, disability, and sexual orientation and gender identity SOGI , among other factors. Exclusion robs individuals of dignity, security, and the opportunity to lead a better life. Unless the root causes of structural exclusion and discrimination are addressed, it will be challenging to support sustainable inclusive growth and rapid poverty reduction.

Poverty is about not having enough money to meet basic needs including food, clothing and shelter. However, poverty is more, much more than just not having enough money. Poverty is lack of shelter. Poverty is being sick and not being able to see a doctor. Poverty is not having access to school and not knowing how to read. Poverty is not having a job, is fear for the future, living one day at a time.

Metrics details. Financial inclusion is a key element of social inclusion, particularly useful in combating poverty and income inequality by opening blocked advancement opportunities for disadvantaged segments of the population. This study intends to investigate the impact of financial inclusion on reducing poverty and income inequality, and the determinants and conditional effects thereof in developing countries. The analysis is carried out using an unbalanced annual panel data for the period of — For this purpose, we construct a novel index of financial inclusion using a broad set of financial sector outreach indicators, finding that per capita income, ratio of internet users, age dependency ratio, inflation, and income inequality significantly influence the level of financial inclusion in developing countries. Furthermore, the results provide robust evidence that financial inclusion significantly reduces poverty rates and income inequality in developing countries. Financial inclusion connotes all initiatives that make formal financial services accessible and affordable, primarily to low-income people.


Poverty and Social Exclusion in India World Bank. https://openknowledge.​ost-west-trikster.org License: CC BY IGO.”.


Social Inclusion

This site uses cookies to optimize functionality and give you the best possible experience. If you continue to navigate this website beyond this page, cookies will be placed on your browser. In every country, some groups confront barriers that prevent them from fully participating in political, economic, and social life. These groups may be excluded not only through legal systems, land and labor markets, but also discriminatory or stigmatizing attitudes, beliefs, or perceptions. Disadvantage is often based on social identity, which may be derived from gender, age, location, occupation, race, ethnicity, religion, citizenship status, disability, and sexual orientation and gender identity SOGI , among other factors.

What is poverty?

Barrier 1: Implicit discrimination

Он почувствовал боль в ногах и сбавил скорость. Дальше бежать было некуда. Как трасса, на продолжение которой не хватило денег, улочка вдруг оборвалась. Перед ним была высокая стена, деревянная скамья и больше. Он посмотрел вверх, на крышу трехэтажного дома, развернулся и бросился назад, но почти тут же остановился. В некотором отдалении от него возникла фигура человека, приближавшегося медленно и неотвратимо. В руке его поблескивал пистолет.

Стратмор глубоко вздохнул. Ясно, что без объяснений ему не обойтись. Она это заслужила, подумал он и принял решение: Сьюзан придется его выслушать.

Сьюзан задумалась о том, почему он задерживается так долго, но ей пришлось забыть о тревоге за него и двигаться вслед за шефом. Стратмор бесшумно спускался по ступенькам. Незачем настораживать Хейла, давать ему знать, что они идут. Почти уже спустившись, Стратмор остановился, нащупывая последнюю ступеньку. Когда он ее нашел, каблук его ботинка громко ударился о кафельную плитку пола.

 Зараженный файл существует, сэр. Но он прошел Сквозь строй. - Если эта система его не перехватила, то откуда вы знаете, что вирус существует. Чатрукьян вдруг обрел прежнюю уверенность. - Цепная мутация, сэр.

Пальцы у него онемели. Он упал. И в следующее мгновение не осталось ничего, кроме черной бездны. ГЛАВА 102 Стратмор спустился на нижний этаж ТРАНСТЕКСТА и ступил с лесов в дюймовый слой воды на полу.

Свет от фары пробежал по цементным стенам. - В главный банк данных попал вирус, - сказал Бринкерхофф.

Из-за чего погибла Меган. Неужели ему предстояло погибнуть по той же причине. Человек неумолимо приближался по крутой дорожке. Вокруг Беккера не было ничего, кроме стен. По сторонам, правда, находились железные ворота, но звать на помощь уже поздно.

Фонтейн кивнул. Иерархия допуска в банк данных была тщательно регламентирована; лица с допуском могли войти через Интернет. В зависимости от уровня допуска они попадали в те отсеки банка данных, которые соответствовали сфере их деятельности. - Поскольку мы связаны с Интернетом, - объяснял Джабба, - хакеры, иностранные правительства и акулы Фонда электронных границ кружат вокруг банка данных двадцать четыре часа в сутки, пытаясь проникнуть внутрь. - Да, - сказал Фонтейн, - и двадцать четыре часа в сутки наши фильтры безопасности их туда не пускают.

Не появится. - Но вы же позвонили… Стратмор позволил себе наконец засмеяться. - Трюк, старый как мир. Никуда я не звонил. ГЛАВА 83 Беккеровская веспа, без сомнения, была самым миниатюрным транспортным средством, когда-либо передвигавшимся по шоссе, ведущему в севильский аэропорт.

 Сьюзан, - наконец произнес он еле слышно.  - У меня нет семьи.

Беккер изо всех сил старался удержаться на шоссе, не дать веспе съехать на обочину. Я должен добраться до ангара. Интересно, увидит ли пилот лирджета, что он подъезжает.

 Его партнер опубликует ключ? - недоуменно переспросила Сьюзан. Стратмор кивнул: - Он разместит его в Интернете, напечатает в газетах, на рекламных щитах. Короче, он отдаст ключ публике. Глаза Сьюзан расширились. - Предоставит для бесплатного скачивания.

 - Это и есть ключ к шифру-убийце. Разница между критическими массами. Семьдесят четыре и восемь десятых. - Подождите, - сказала Сьюзан, заглядывая через плечо Соши.

Там, в темноте, ярко сияла клавиатура. Стратмор проследил за ее взглядом и нахмурился Он надеялся, что Сьюзан не заметит эту контрольную панель. Эта светящаяся клавиатура управляла его личным лифтом. Стратмор и его высокопоставленные посетители попадали в шифровалку и уходили незаметно для остальных сотрудников.

Беккер получил четкие инструкции: ни к чему не прикасаться, ничего не читать. Просто все привезти. Абсолютно .

А я-то думал, что ты будешь это отрицать. - Подите к черту. - Очень остроумно. - Вы болван, Стратмор, - сказал Хейл, сплюнув.  - К вашему сведению, ваш ТРАНСТЕКСТ перегрелся.

 Конечно, - чуть слышно сказала.  - Танкадо подумал, что раз мы приостановили действие его страхового полиса, то можем приостановить и его. Постепенно она начала понимать.

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3 Comments

  1. ThГ©ophile G.

    Halsey Rogers,

    23.04.2021 at 14:59 Reply
  2. Zachary B.

    Townsend Centre for International Poverty Research.

    23.04.2021 at 15:37 Reply
  3. Jesse T.

    All over the world, people are prevented from participating fully in society through mechanisms that go beyond the structural and institutional barriers that rational choice theory identifies —poverty, exclusion by law or force, taste-based or statistical discrimination, and externalities from social networks differentiated by socioeconomic status.

    24.04.2021 at 13:55 Reply

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