Journal of Policy Modeling最新文献

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.

Foreign currency borrowings by emerging market corporations have increased significantly post-global financial crisis. Extant literature has mainly focussed on the flow of foreign currency borrowings, and policies which control the volatility of the flow of the foreign currency borrowings. In this paper, we emphasize the stock of the foreign currency borrowings in the balance sheet of a firm instead of the flow of the foreign currency borrowings, and show the ineffectiveness of policies focused on controlling the flow of foreign currency borrowings. We use the data of non-financial Indian firms listed in the Bombay Stock Exchange and National Stock Exchange. Our analysis show the fallacy of a policy focussed on controlling the flow of foreign currency borrowings. Despite policies which control the flow of the foreign currency borrowings, if a firm has a high stock of foreign currency borrowings in their balance sheet then the financial risk associated with the firm increases. A possible implication of our results is that too much foreign currency borrowings may pile up the risk in the financial system which may become a cause of concern.

Semi-subsistence households in developing countries play a considerable role as both producers and consumers of agricultural products, with a substantial part of their consumption contributed by home production for home consumption (HPHC). This study employs a modeling framework that integrates an HPHC augmented database with a modified economywide model that accommodates the distinct features of these households. Results from model simulations with border price shocks and several policy responses indicate that farm households are less influenced by external price shocks but are more responsive to enhancements in the local marketing system. Subsidies to strategic non-food imports during soaring prices appear less effective in inducing agents to engage in production. This finding suggests that the welfare gains reported by studies on price incentives locally, and agricultural policy reforms in developed market economies are likely to be large overestimates of the welfare implications for semi-subsistence households in many of the least developed economies.

We design a self-selection-pricing mechanism in which an electricity supplier offers its customers an optimal menu of contracts subject to a price ceiling set by the government, a hybrid model of market mechanism and government controls. We calibrate the model using information from a residential electricity market in China. Our mechanism outperforms the tiered-electricity-pricing system in China in terms of environmental and industrial sustainability but comes at the cost of providing less protection for low-income households (i.e., less equity). We conclude by offering measures of sustainability and equity that governments could use when trying to balance the trade-off between the two.

This paper analyses the auction policy over enrollees’ monopoly rights introduced in the Chilean pension system. This policy was designed to promote competition in the pension fund market driven by private firms, after 30 years of operation. Since the Chilean pension fund system has inspired dozens of countries in the last forty years, the analysis of the design and performance of its relatively new auction mechanism is of worldwide interest. We present a theoretical and empirical model. Our theoretical model illustrates firms’ incentives to participate in the auction process. Our empirical analysis focuses on the effect of auctions on outcomes, such as fees, mark-ups, demand price elasticity, returns, and risk premiums. Despite the evidence shown for the positive benefits of the auction implementation, the current mechanism design is not considering that the biggest issue is the low individuals’ price response levels. Importantly, the current auction design only incentivizes new entrants to participate. Thus, the design generates low competition in the auction processes. Proper design should incentivize all firms to participate. Besides, we find that consumers’ price elasticity increased after the implementation of auctions, although demand is still generally inelastic. Interestingly, non-winning auction firms did not react in fees but may have reacted in other characteristics, such as returns and risk premiums.

Public infrastructure procurement is a crucial policy tool, a prerequisite for public and private investments and for economic and social capital growth. Low performance in execution severely hinders infrastructure provision and benefits delivery. One of the most sensitive phases in public infrastructure procurement is the design because of the strategic relationship that it potentially creates between procurers and contractors in the execution stage, affecting the costs and the duration of the contract. In this paper, using recent developments in non-parametric frontiers and propensity score matching, we evaluate the performance in the execution of public works in Italy. The analysis provides robust evidence of significant improvement of performance where procurers opt for design and build contracts, which lead to lower transaction costs, allowing contractors to better accommodate the project in the execution. Our findings bear considerable policy implications.

Due to its focus on prediction rather than causal inference, machine learning has long been treated somewhat neglectfully in the economic literature. For several reasons, however, interest in machine learning has surged recently and is slowly finding its way into the econometric toolbox. Within the economic literature, regional integration has been one of the research areas at the forefront of this development, with various studies experimenting with different machine learning techniques to shed light on the complex dynamics governing regional integration processes. This paper provides the first systematic review of the literature that uses machine learning to study regional economic integration. The focus is twofold, first analysing studies along various thematic and methodological features (and the links between them), and then discussing the scope and nature of policy insights derived from the surveyed body of literature.