In the realm of macroeconomics, investment is universally acknowledged as a fundamental pillar of economic progress, as it plays a paramount role in fostering productivity. The capacity of investment to propel and invigorate other facets of production necessitates a comprehensive understanding of the pivotal function that investments serve in fortifying productive efficiency and driving forward technological advancement. With this in mind, our study endeavors to address the pressing research question of whether aggregated and disaggregated foreign direct investment (FDI) and domestic investment (DI) have the potential to stimulate total factor productivity (TFP) in Pakistan. We adopt the simulated dynamic autoregressive distributed lag (SARDL) model approach to analyze data spanning from 1990 to 2023. Our empirical results substantiate the positive and significant impact of disaggregated external FDI (including primary, secondary, and service sectors) in bolstering Pakistan’s total factor productivity in both the short and long term. Similarly, aggregated domestic investment demonstrates a positive and significant effect on TFP in both the short and long run. However, when assessed at the disaggregated level (namely private and public investment), public investment displays a positive, albeit statistically insignificant, impact on TFP, while private investment shows a negative and insubstantial effect on TFP in both the short and long run. By adopting control variables such as labor efficiency, human development index, innovation, and inflation, our empirical findings reveal a significant and positive effect of these variables on TFP in the long term. To strengthen the robustness of the research, a counterfactual analysis is performed to assess the effects of changes in predictors on the projected variable over the forecasted 30 years. Furthermore, to ensure robustness check, we apply the KRLS machine learning algorithm approach to investigate the pointwise marginal effects of independent variables on the dependent variable. Overall, our research reinforces the significance of investment in enhancing Pakistan’s total factor productivity.
While conventional approaches to Service Failure and Recovery (SFR) predominantly rely on basic surveys and scenario-based experiments, recent advancements in failure recovery found in related fields like Industry 4.0, AI-enabled decision support and digital service systems have presented intriguing possibilities (Wang et al., 2024; Zhang, 2024). Against this backdrop, this study proposes a novel methodology that leverages the rapidly evolving domain of smart maintenance and knowledge-based capability to establish a fresh framework for SFR. The suggested framework consists of seven distinct modules, namely Monitoring, Predictive and Preventive, Service Failure Detection, Failure Report, Diagnosis, Prognosis, and Healing Support. This investigation delineates the key functions and activities associated with each module, elucidates the information flows between them, and outlines their interface with service providers, customers, suppliers, and clients. Additionally, it delves into the considerations and implications arising from the proposed framework.
Rice is the primary staple crop of the population and represents nearly two-thirds of cereal imports in Senegal, a net food importer. Domestic production capacity is limited due to the prevalence of small-scale agriculture, characterized by farms of less than one hectare. Despite government initiatives to increase cultivated land and attain self-sufficiency, the scale of rice cultivation is significantly restricted by several factors, including limited access to credit and tenure insecurity. This study investigates the extent to which land access conditions the effect of credit on both the extensive and intensive margins of the adoption of improved and certified rice varieties’ investment decisions. Drawing on secondary data from the 2022 Annual Agricultural Survey in Senegal, the analysis employs a double-hurdle model to provide empirical estimates. In the full sample, access to credit is not significantly associated with either the adoption decision or adoption intensity on average, a null result that masks important heterogeneity. Conditional on observed household and farm characteristics, credit access is positively and significantly associated with both the adoption decision and adoption intensity among tenure-secure households. Among tenure-insecure households, credit access is negatively associated with the adoption decision, a pattern consistent with credit reallocation toward other obligations, crop-choice tradeoffs under binding land constraints, and heightened debt-induced risk aversion. Robustness checks using Oster’s delta (2019) and the Altonji-Elder-Taber ratio confirm that these conditional associations are resilient to potential omitted variable bias. These results highlight the critical role of tenure security in mediating the relationship between agricultural financing and technology adoption and motivate the joint design of credit and land tenure reform policies.
Resource-rich nations often experience slower economic performance instead of leveraging their natural wealth for economic advancement, a concept known as the resource curse. Human capital and the quality of institutions are pivotal in explaining this paradox, as their effectiveness determines whether natural resources exacerbate or mitigate the resource curse. This research focuses on how natural resources, human capital, and institutional quality interact to influence economic performance across 127 developed and developing nations from 1996 to 2020. Using the Method of Moments Quantile Regression (MMQR), we examine the resource–income nexus across different positions of the economic performance distribution. The findings reveal that resource rents are positively associated with economic performance in developed countries, supporting the resource-blessing hypothesis, whereas they have a negative association in developing countries, consistent with the resource-curse hypothesis. Human capital positively moderates the resource–income relationship in developing countries, suggesting that greater human capital can weaken the resource curse, while its interaction with natural resources is negative in developed countries. Institutional quality independently promotes economic performance in both groups; however, contrary to the hypothesized buffering role, its interaction with natural resources is negative and statistically significant in both developed and developing countries. Thus, stronger institutional quality does not mitigate the adverse resource effect in developing countries and reduces the positive resource-income association in developed countries. These findings highlight the importance of combining human capital development with economic diversification and resource-management strategies rather than relying on institutional quality alone to transform resource wealth into economic performance.
