Journal of Policy Modeling最新文献

Corruption remains a major challenge to sustainable economic growth, good governance, peace, and stability in both developed and developing countries. However, in developing countries, and particularly in Africa, hunger is another big challenge to inclusive economic development. To date, no empirical study has examined the effects of different types of corruption on hunger. Using three types of corruption (executive, legislative, and judicial corruption dynamics) and a panel of 45 African countries, this study contributes to the literature on the effects of corruption by examining, as a first attempt, the impact of types of corruption on hunger. We address the weak time-variance of our main regressors by using the most recent sequential linear panel dynamic estimator. The results show that countries with higher levels of executive, legislative, and judicial corruption are associated with a higher level of hunger. Moreover, the results show that executive corruption is the most disastrous for hunger in Africa, followed by legislative corruption. Our results remain valid even after using alternative measures of the key variables (hunger and corruption) and after controlling for the dynamic endogeneity using the generalized method of moments. Further analysis provides strong evidence that the political distribution of power across social groups mitigates the effect of corruption on hunger.

Earlier empirical studies examining the impact of exchange rate misalignment on economic growth were based on a symmetric approach, assuming that undervaluation and overvaluation affect economic growth symmetrically. However, recent empirical studies have shown that exchange rate misalignments asymmetrically affect economic growth. This study, therefore, examines the asymmetric effects of real exchange rate misalignments on economic growth in Turkey. The asymmetric effects of the non-linear autoregressive distributed lag model show that both overvaluation and undervaluation impede economic growth in Turkey. The study recommends that Turkey should maintain a market-based exchange rate policy to reduce currency misalignment. The study also recommends that the central bank of Turkey should intervene in the foreign exchange market for a short-term to mitigate the excessive distortions in exchange rates and avoid inefficiencies in resource allocation.

The average education expenditure of each child accounts for more than half of the family's per capita income in China and has held back the fertility intentions. Will the decree on unloading the burden of extracurricular tutoring raise future fertility willingness in China? Using China Family Panel Studies (CFPS) cross-sectional data in 2018, we simulate the effects of reduction in extracurricular tutoring hours and expenses on fertility behavior. The results reveal that extracurricular tutoring explains low fertility rate in China. The mothers in the one-child families are less likely to have a second birth due to participation in job markets and threshold in their career. The willingness of giving birth to a second child is remarkably increased along with the reduction in extracurricular training activities, especially for urbans. Reduction in tutoring expenditure plays a bigger role in adults' second-child desire than do tutoring hours.

Against a backdrop of debt ratio targets being central to recent proposed changes to the EU fiscal rules, we examine errors in official forecasts of the General Government debt ratios and their determinants in 26 member states from 2012 to 2019 when the “six pack” rules applied. We find debt ratio outturns exceeding projected values with forecast errors increasing over a four-year horizon. Larger errors arise where the initial debt ratio exceeds the Maastricht Treaty threshold of 60 per cent. In modelling the forecast errors of the debt ratio, we find that most of the variation is explained by forecast errors in the output growth rate and in the structural budget balance, as well as previous errors in projecting the debt ratio. During the sample period, member states who had not met their medium-term objective of a balanced structural budget were expected to adhere to a net expenditure rule. For countries subject to this requirement, we find undue optimism arising in forecasting the deficit ratio, a determinant of the debt ratio. The implications of these findings for EU policymakers and, in particular, forecasters are considered.

We identify seven global value chain (GVC)-related challenges faced by the least developed countries (LDCs) of the Association of Southeast Asian Nations (ASEAN) region. The LDCs face some of the most rudimentary challenges related to trade participation and competitiveness. The challenges identified in the paper have been empirically validated using Fuzzy AHP modelling to decipher the priority weights. The findings reveal that ‘infrastructural and logistical constraints’ is the most imperative challenge followed by ‘limited FDI inflows’ and ‘inadequate development of SME clusters. The remaining challenges include: inadequate aid-for-trade, dismal LDC participation through the RTA/FTA route, lack of robust industrial policy, constraints in value chain upgradation, limited FDI. The study is beneficial for industry and provides useful inputs for policy-making. It helps in ascertaining optimal resource allocation for the purpose of enhancing trade competitiveness and economic development.

This study simulates the impact of the change in trade policy between the US and China on the trade volume and economic prosperity of Sub-Saharan Africa (SSA). To do that, we employ a Computable General Equilibrium (CGE) model based on the Global Trade Analysis Project (GTAP) with different scenarios focusing on increases in tariffs. The results show that the tariff increases negatively affect the US and China in terms of trade volume and economic growth, while it leads to trade diversion and creation for the SSA. This offers valuable opportunities in improving exports and economic growth, particularly for Ethiopia, Kenya, and Nigeria. On the sectorial level, the findings imply that agriculture, food, and oil and gas sectors are positively affected in terms of export volume, while mineral, metal and service sectors are negatively impacted by the trade war.

This paper uses a recursive dynamic general equilibrium model to study the impact of the 2015 terrorist attacks in Tunisia. It examines the government’s fiscal responses: increased security spending and the reduction of the tourism sector’s value-added tax (VAT) rate. It finds that these responses accounted for a significant share of the attacks’ total cost. The results also underscore the need for a comprehensive approach to addressing the economic consequences of terrorism. Increased security spending mitigates future risks but does not directly help the affected sector. Direct support to the sector by reducing VAT has an immediate and positive impact.

This paper seeks to assess the transformative potential of Artificial Intelligence (AI) in policy modeling. Rapid advancements in AI, encompassing algorithms, advanced programming software, robotics, metadata, sophisticated mathematical models, neural networks, and graphical models are ushering in innovative new research methods for analysing and resolving intricate socio-economic issues. Our focus lies in a comparative evaluation of Artificial Intelligence Response (AIR) versus Human Intelligence Response (HIR) in generating swift and potent solutions to various socio-economic challenges. To achieve this, we propose a fundamental model for appraising the effectiveness of policy modeling, known as the "Policy Modeling Response Evaluator (PMR-Evaluator)." Furthermore, we conducted an experiment to gauge the responsiveness and effectiveness of both AIR and HIR. This experiment revolved around addressing a specific socio-economic problem, namely controlling inflation. Initially, we scrutinized responses from an extensive database of papers published in the Journal of Policy Modeling (JPM) by Elsevier over the past forty-five years (1978–2023) to ascertain HIR's capacity to analyze and resolve inflation-related issues. Concurrently, we utilized ChatGPT, a powerful artificial intelligence application (AI-APP), to explore potential solutions for controlling inflation. Ultimately, we analyzed whether HIR or AIR proved more effective and precise.

We investigate the extent to which various structural risks exacerbate the materialization of credit risk and affect financial cycle downturns. We use a large database covering all sorts of cyclical and structural features of the financial sector and the real economy for a panel of 30 countries over the period 2006Q1–2019Q4. We show that elevated levels of structural risks may have an important role in explaining the severity of credit risk materialization during financial cycle contractions. Among these risks, private and public sector indebtedness, banking sector resilience and concentration of real estate exposures stand out. Moreover, we show that the elevated levels of some of the structural risks identified may be related to long-standing accommodative economic policy. Our evidence implies a stronger role for macroprudential policy, especially in countries with higher levels of structural risks.

Agriculture is under transformation in sub-Saharan Africa where millions still do not have access to a healthy diet. Policy makers in this region should find ways to accelerate agricultural transformation while increasing access to healthy diets. Optimizing agriculture’s public budget stands out as a handy option. By combining a dynamic computable general equilibrium model and a multi-criteria decision-making technique, and applying them in the context of Ethiopia, this paper points to an important trade-off that policy makers should keep in mind. An optimal allocation of agriculture’s public budget aimed at increasing agri-food output, creating off-farm jobs and reducing rural poverty, which are agricultural transformation objectives, will help to reduce the cost of a healthy diet, allowing around 2 million more Ethiopians to afford it. This number could even be higher should policy makers allocate the budget optimally aiming at only lowering the cost of a healthy diet, but at the cost of reducing household income and slowing down transformation.