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Malaysia is one of the high performing economies (HPE) in Southeast Asia. It had experienced strong growth and development for the period between 1957 and 1995. Socioeconomic planning, structural and trade adjustments, and adoption of pragmatic policies that promoted agriculture as well as the manufacturing sub‐sector resulted in higher productivities, incomes and standards of living. Policymakers were also successful in adopting policies that mitigated poverty and, to a lesser extent, decreased income inequality.

The farm sector is crucial for rural poverty alleviation, alongside the non-farm sector, which contributes to mitigating risks associated with crop failures. This paper investigates the effects of public policies on productive employment within both the farm and non-farm sectors in sub-Saharan Africa.

A meta-analysis is conducted exclusively on the results of the Partnership for Economic Policy (PEP)-funded studies under the Policy Analysis on Growth and Employment (PAGE II) initiative. Selected studies focused on the impact of public policies on productive employment in rural farm and non-farm sectors, encompassing a total of nine sub-Saharan Africa countries in: Benin, Burkina Faso, Cote d'Ivoire, Democratic Republic of Congo, Ghana, Lesotho, Nigeria, Senegal and South Africa.

The results indicate that public investments in rural areas and public policies that facilitate access to productive resources are likely to enhance productive employment. The overall effect size is positive and significant, ranging from 2% to 10% increases in productive employment. Sources of variation include the sector of activity and the policy instrument. In addition, the policy effects are gender-sensitive and seem more consistent in the non-farm sector.

Although the selected working papers addressed several aspects of productive employment, other aspects warrant further investigation. Policies involving restrictions or regulations have received little attention in the impact analysis. Researches to fill this gap would be important. Another suggestion for further research is the analysis of the relative importance of non-farm employment in rural areas in developing countries. It is always assumed that rural households depend heavily on agriculture for their subsistence.

The contribution of the paper lies in the comparative analysis of numerous public policies implemented in nine distinct countries. By consolidating data from fourteen 14 different experiences into a single study, the paper offers valuable insights on factors that determine policy effectiveness and contribute to understanding what worked for whom and why.

This paper investigates the impact of bank credit on agricultural productivity in the Central African Economic and Monetary Community (CEMAC) from 1990 to 2019. Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting.

Agricultural value added (AGRVA) to the gross domestic product (GDP) proxies agricultural productivity while domestic credit to the private sector by banks (DCPSB), broad money supply, land, inflation (INF), physical capital (PHKAP) and labour supply are explanatory variables. The autoregressive distributed lag technique is utilized.

The co-integration test results show a long-run co-integration among the variables. The findings disclose that DCPSB, land and PHKAP impact positively on the AGRVA. Broad money supply, INF and labour impact negatively on the AGRVA to the GDP.

The results suggest that the CEMAC governments should encourage effective ways to increase bank credit flow to private enterprises in the agricultural sector through efficient bank's intermediation.

The governments should create more agricultural banks and improve the operation of existing ones to ensure direct credit to agricultural activities. The Bank of Central African Economic and Monetary Community should apply aggressive policy which eliminates all the bottlenecks undermining credit flow to the private sector in mutualism with agricultural productivity.

The commercial banks should give more credit to private sector to mutually benefit the agricultural sector and the banking sector. The governments of the CEMAC economies should expand funding into the capital market which considerably boosts agricultural productivity.

Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting; some reveal positive impacts, some show negative impacts and others indicate U-shape behaviour. Hence, research is required to fill the lacuna.

The purpose of this paper is to estimate the determinants of rural and national poverty, of income distribution, and of agricultural growth in developing countries.

Data for all variables are from the 2008 World Development Report. The author applies the least‐squares estimation technique in a multivariate linear regression.

It is found, from different size samples, that: the percentage of the rural population living below the national rural poverty line in a developing country is dependent upon the logarithm of per capita purchasing power parity gross national income and the region in which it is located; it linearly depends on its per capita agriculture value added and its geographic location; agriculture value added growth linearly depends on the share of women in the agricultural labor force, whether the developing country is agriculture‐based, and whether it is located in Europe or Central Asia; and agricultural productivity linearly depends on the amount of arable and permanent cropland per agricultural person, the share of women in the agricultural labor force, and the share of agricultural employment in total employment.

Statistical results in this paper will assist governments in developing countries assess the magnitude of agricultural policy variables in an effort to use agriculture as an engine for economic development.

The purpose of this study is to measure the effect of land degradation and the environmental changes on agricultural productivity in Somalia, as well as the other factors that affect crop production in Somalia.

Cobb-Douglas production function assumes crop production as a dependent variable and land degradation, labor, capital, fertilizer and climate change as the explanatory variables. In this study time-series data (1962–2017) collected from the Food and Agriculture Organization and World Development Indicators were used. The unit root of the data was examined using Ng-Perron and the Lee-Strazicich methods to explore the unit root property of the breaks. Structural breaks are observed using the Chow test, and the long-run relationship between the variables is examined using Gregory and Hanssen's approach.

This study found that land degradation and climate change have a negative relationship with agriculture production in Somalia. Land degradation leads to the decline in agricultural production as the loss of one hectare of land due the depletion causes agriculture production of Somalia to fall by about five percent. Climate changes and warming of the environment lead to the reduction of agriculture production. One degree Celsius rise in the temperature leads to a three percent decline in agricultural production. Capital contributes immensely to agricultural production as one unit of additional capital raises production by seven percent. The contribution of labor to agricultural production is limited because of land contraction

Land degradation is a significant contributor to the decline of agricultural production. As land degradation continues to worsen, rural poverty increases, which in turn causes the rural migration and the social conflict. The government should develop land improvement programs such as increasing market orientation of the farmers, encourage private sector engagement in agribusiness and establish a regulatory framework of the land uses.

This study examines the structure of the time-series and specifies the break periods to determine when and where significant and sudden changes occurred within land degradation and agricultural production. The study employs advanced econometric methods, namely, Ng-Perron method and the Lee-Strazicich method to test the unit root property of the breaks. It also examines the long-run relationship between the variables using Gregory and Hanssen's approach.

The different types of estimators of rational expectations models are surveyed. A key feature is that the model′s solution has to be taken into account when it is estimated. The two ways of doing this, the substitution and errors‐in‐variables methods, give rise to different estimators. In the former case, a generalised least‐squares or maximum‐likelihood type estimator generally gives consistent and efficient estimates. In the latter case, a generalised instrumental variable (GIV) type estimator is needed. Because the substitution method involves more complicated restrictions and because it resolves the solution indeterminacy in a more arbitary fashion, when there are forward‐looking expectations, the errors‐in‐variables solution with the GIV estimator is the recommended combination.

World legends and the scientific community have taken the devastating impact of poverty issue seriously which has been reflected in the growing trend of research in this area. Hence, this paper aims to conduct a bibliometric analysis on poverty alleviation literature, discuss the various dimensions of poverty alleviation and deliver some ideas for future research.

This study deploys a combined quali-quantitative method familiar as meta-literature review on 454 articles collected from the Web of Science (WoS) database with Social Science Citation Index (SSCI) coverage over the period 1971–2020. Using Rstudio, VOSviewer and Excel, the collected data have been analysed from different lenses.

This study considers the most contributing scientific actors like authors, journals, topics, institutions and countries as parameters for analysing articles. Based on the analysis from various perspectives, it determines five main research streams upon which it provides some potential research directions to be considered in future research.

This study solely relies on the articles available in the WoS database with index in SSCI. However, it excludes analysing thousands of articles on the same topic available in other platforms.

This study provides a retrospective on the scientific works and collective efforts of scholars germane to poverty alleviation from the highest ranked journals, which would help better understand the literature development and the intellectual structure of this field.

The purpose of this paper is to examine the relationship between industrial sector growth, inequalities and urban poverty reduction

The paper used static panel data analysis. However, the tests suggest that there are no state-specific effects; hence, the pooled panel regression techniques are used for the analysis.

The findings of the paper suggest that the industrial sector growth exert no significance on urban poverty while the urban wholesale and retail services growth is found to be substantially strong in reducing urban poverty. The results also indicate that there is no statistically significant evidence to conclude that higher incidence of urban poverty was due to the high degree of inequalities.

This paper has provided some helpful results in understanding the heterogeneous effects of sectoral components of growth of urban poverty in the presence of high income inequalities, but the limitation of this study is that there is no disaggregated poverty and growth data on different occupational activity.

There is a need to expand investment in the production and export manufacturing labor-intensive sectors; this will help increase the labor absorption rate of the industry and, thus, reduce poverty in the urban areas.

The paper improves on previous research on poverty in Nigeria by explicitly recognizing the effects of location and inequality.

This note shows that much conventional macro‐economic literature uses two inconsistent definitions of equilibrium in the commodity market. Equilibrium is defined as income equalling expenditure when deriving the IS curve; but when overall equilibrium is treated the requirement for equilibrium is that planned supply equals planned demand. The note shows that these inconsistent definitions lead to a confusing and often erroneous exposition of disequilibrium behaviour.

The purpose of this paper is to evaluate the relative importance of different sources of finance for agricultural and non-agricultural investments using unique Smallholder Financial Diaries collected by Consultative Group to Assist the Poor (CGAP) in Mozambique, Pakistan and Tanzania at the individual and household level.

Following the analytical framework of variance decomposition developed in Samphantharak and Townsend (2010), this study develops a method to quantify how much each cash deficit associated to investments and expenses of interest co-move with different financing sources.

This paper finds that self-finance, rather than formal or informal finance from external providers, is the main financing source for long-term and short-term smallholder agricultural investments. Further, the paper finds that the main source of self-finance varies depending on the economic opportunities faced by smallholders, with non-agricultural income as the dominant financing source for some, while agricultural income dominating for others.

Given CGAP’s Smallholder Financial Diaries is not nationally representative, research results should be interpreted carefully. However, to the best of the authors’ knowledge, this is the first paper to analyze financing sources for smallholder households making use of high frequency financial data for individuals in developing countries.

These findings imply that financial inclusion policies specifically targeting smallholders and the agricultural sector would benefit from enabling the development of an ecosystem of diverse financial services that respond simultaneously to both agriculture and non-agriculture needs.

This is paper furthers the authors’ knowledge on how smallholder households are financing their agricultural investments. Moreover, it applies methods in new ways to exploit a unique data set.