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The purpose of this paper is to explore the matching relationship between factor endowment and industrial structure, and its impact on economic growth.

The assortative matching method is developed to quantitatively measure the matching between factor endowment and industrial structure. A series of empirical tests are then carried out to evaluate the impact on the economic development of the matching.

1) The matching between factor endowment and industrial structure has a significantly positive impact on economic growth. (2) Economic growth reaches its maximum when the gap between the two sectors narrows to zero. (3) This effect is particularly significant for countries with higher GDP per capita and GNI per capita. (4) The results remain robust after employing a series of tests.

Aggressive industrial policies are not desirable. The optimal industrial structure is the one that complied with the comparative advantage of the given factor endowment in the economy.

So far, there has been a significant lack of an applicable quantitative indicator for measuring the matching between factor endowment and industrial structure, which is essential for conducting empirical tests and providing evidence for related economic theories.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

The main aim of this paper is to verify whether the modern mainstream economic theory of multinational enterprise that explains foreign direct investment (FDI) from developed countries is also able to account for investment decisions of multinational enterprises (MNEs) from emerging economies.

Using Knowledge-And-Physical-Capital (KAPC) model as an analytical framework and Poisson-pseudo maximum likelihood estimation technique, the authors identify determinants of FDI flows from emerging economies. The data set consists of 38 home and 134 host countries during the period 2000–2012. Empirical evidence supports high explanatory power of KAPC model. Further, compared with the earlier Knowledge-Capital (KC) model, results confirm the importance of physical capital.

The estimation results confirm the hypothesis that mainstream economic theory can explain FDI flows from the emerging economies by highlighting the roles of total market size, skilled-labor abundance, investment and trade costs and geographical distance between two countries.

This study casts doubt on the alternative way that the KAPC model suggests to distinguish between horizontal and vertical FDI. The argument that horizontal MNE headquarters would be relatively more abundant than vertical MNE headquarters in countries that are abundant in physical capital relative to skilled labor seems reasonable but the idea of variable specification in the estimated equation should be revised.

Firms should be allowed to move their resources freely into and out of specific activities, both internally and internationally across border. To reach that goal, governments of potential host countries can adopt several measures, most importantly remove restrictions on payments, transfers and capital transactions and open previously closed industries to welcome foreign investment. In addition, to improve investment climate in general, governments need to pay attention to enhancing security of property rights, regulating internal taxation (i.e. corporate income tax), guaranteeing adequacy of infrastructure, efficient functioning of finance and labor markets and fighting against corruption.

The location choice of emerging investors set priority on similarity in economic size, geographical and cultural proximity. It is because shared borders or common official languages would reduce information costs and enhance information flows. Also, investors consider horizontal FDI (with motivation to expand market demand) as one of main modes of entry into a foreign market and a substitute for export. Likewise, distance is often understood as an important investment friction.

The outstanding contribution is that the research has uncovered the positive and statistically significant effect of physical capital on FDI activity, which has not been discussed in the earlier KC model. However, at the same time, the study casts doubt on the KAPC model's argument that relative abundance in physical capital to skilled labor between two countries determines FDI types and suggests that this argument and its empirical model specification should be carefully reviewed.

Agriculture in Ethiopia relies heavily on traditional farm power sources and is designated by the lowest farm machinery access, in contrast to other Sub-Sahara African (SSA) countries. The purpose of this research is to analyze the heterogeneity of mechanization service transactions and factors determining farmers' cooperation in mechanization clusters and willingness to accept land consolidation.

The authors conducted a cross-sectional survey of producer households in major crop production areas in the Oromia, SNNPR, Amhara and Tigray regions. The sampling design involved three stages: districts were selected using a stratified sampling approach accompanied by simple random samples of kebele units and producer households in the second and final stages, respectively.

This study’s results show that mechanization service costs, service relationships, clustering and land consolidation exhibit significant heterogeneity across the study areas. Cluster farming was found to be advantageous against diseconomies, rationalized by upgrading the mechanization scale. The probit model parameterization of the probability distributions reveals that household, land, crop, mechanization service, remoteness and location-related factors determine participation in mechanization clusters and willingness to accept land consolidation.

Fostering cooperation by focusing on constraints and demand of users is suggested to reduce transaction costs and expand hired mechanization services to unaddressed areas. The findings are relevant to most SSA countries where mechanization development is hampered by land fragmentation.

Limited information is available on agricultural mechanization development for smallholder farmers, particularly in Ethiopia, and this study adds empirical evidence about the synergy between cluster farming and mechanization, horizontal coordination and alternative supply models.

This study examines the relationship between investors' familiarity bias, including the home bias and endowment bias, and their financial situations, expectations and personal characteristics.

Using the 2019 Survey of Consumer Finances, the authors utilize an ordinary least squares regression to identify the presence of endowment bias and home bias in individual investors' direct stock holdings and use a Heckman selection model to examine determinants of the extent of endowment bias and home bias.

This study finds that investors with higher income and more education, men, non-white investors and people with greater risk tolerance are actually at a greater risk of endowment bias. This study also identifies a profile of investors that are more likely to have a home bias: with less financial sophistication, lower net worth, older, female, more risk-averse, with a positive expectation about the domestic economy and a relatively shorter investment horizon.

This paper is among the first to use US investors' directly reported stock holdings to examine the individual characteristics that are correlated with greater familiarity bias, providing financial professionals with information about how to allocate their limited time in providing education to a variety of clients.

With heterogeneous findings dominating the growth and natural resources relations, there is a need to explain the variances in Africa's growth process as induced by robust measures of factor endowments. This study used a comprehensive set of data from the updated database of the World Bank to capture the heterogeneous dimensions of natural resource endowments on growth with a particular focus on establishing complementary evidence on the resource curse hypothesis in energy and environmental economics literature in Africa. These comprehensive data on oil rent, coal rent and forest rent could provide new and insightful evidence on obscure relations on the subject matter.

This paper considers the panel vector error correction model (PVECM) procedure to explain changes in economic growth outcomes as induced by oil rent, coal rent and forest rent. The consideration of the PVECM was premised on the panel unit root process that returns series that were cointegrated at the first-order differentials.

The paper found positive relations between oil rent, coal rent and economic development in Africa. Forest rent, on the other hand, is inversely related to economic growth in Africa. Trade and human capital are positively related to economic growth in Africa, while population growth is negatively associated with economic growth in Africa.

Short-run policies should be tailored towards the stability of fiscal expenditure such that the objective of fiscal policy, which is to maintain the condition of full employment and economic stability and stabilise the rate of growth, can be optimised and sustained. By this, the resource curse will be averted and productive capacity will increase, leading to sustainable growth and development in Africa, where conditions for growth and development remain inadequately met.

The originality of this paper can be viewed from the strength of its arguments and methods adopted to address the questions raised in this paper. This study further illuminated age-long obscure relations in the literature of natural resource endowment and economic growth by taking a disaggregated approach to the component-by-component analysis of natural resources factors (the oil rent, coal rent and forest rent) and their corresponding influence on economic growth in Africa. This pattern remains underexplored mainly in previous literature on the subject. Many African countries are blessed with an abundance of these different natural resources in varying proportions. The misuse and mismanagement of these resources along various dimensions have been the core of the inclination towards the resource curse hypothesis in Africa. Knowing how growth conditions respond to changes in the depth of forest resources, oil resources and coal resources could be useful pointers in Africa's overall energy use and management. This study contributed to the literature on natural resource-induced growth dynamics by offering a generalisable conclusion as to why natural resource-abundance economies are prone to poor economic performance. This study further asks if mineral deposits are a source or reflection of ill growth and underdevelopment in African countries.

Despite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.

This study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.

The adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.

This study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The Persons with Disabilities (PWDs) Act, 2006 (Act 715) was passed in Ghana to grant several rights to PWDs, including access to public services such as healthcare. This paper investigates the inequality in resources and then later assesses the effect of disability on healthcare utilization if all resources are distributed equally between disabled and not disabled persons.

The study uses data from the seventh round of the Ghana Living Standards Survey (GLSS 7), which was conducted in 2016/2017, and employs the estimation method of propensity score matching (PSM), within the framework of the capability approach (CA).

The findings are that there is a disparity in the resources and conversion factors needed to utilize healthcare. Compared to not disabled persons, persons living with disability are more likely to be poorer but pay more out of pocket because they are more likely to be uninsured. They are also older, male, uneducated and live in rural areas. They are also likely to spend more money but less time to travel to the health facility, and they wait longer to receive treatment. After matching these background characteristics, disability reduces healthcare utilization by 12.4%.

The research is limited by the lack of information about the reasons for seeking healthcare by the persons living with disability, whether it is for general treatment as any other person or for treating the disability.

Persons with disability are less endowed. However, even if they have the same resources as their abled counterparts, disability will still reduce healthcare utilization.

This paper identifies and addresses all forms of inequality with respect to healthcare utilization, within Amartya Sen’s Capability Approach.

Persons living with disability are less likely to seek treatment when ill. This is understandable since there is a disparity in the resources and conversion factors needed to utilize healthcare. However, after matching these background characteristics, just being disabled still reduces healthcare utilization. The paper uses Sen’s CA framework.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2022-0084

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.