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The design of effective policies that increase access to agricultural credit should consider understanding credit constraint farmers’ groups and their response to changes in the credit conditions. To contribute to this understanding, this study surveyed farmers from Chile and classified them into five credit constraint categories discussed in credit literature. In addition, these farmers indicated how they would react to a series of hypothetical conditions related to changing interest rates, loan maturity and grace periods. Their responses were employed to measure credit demand scores (i.e. relative elasticities). Regression tests evaluated how different types of farmers reacted to changing credit conditions.

Farmers from Chile were surveyed using a mix of random and convenience sampling. Surveyed farmers were classified into five credit constraint categories proposed by previous research. Farmers rated their demand for credit on a five-point Likert-type scale for hypothetical changes in interest rates, loan maturities and grace periods. Their responses were employed to measure credit demand scores or relative credit elasticities. The study evaluated credit elasticity as a function of farmers’ credit constraint and some control variables using several regressions, including OLS, ordered probit and hierarchical regression.

The study identified 44% unconstrained nonborrowing farmers, 23% unconstrained borrowers, 14% quantity-constrained, 16% risk-constrained and 3% transaction cost-constrained farmers. Unconstrained borrowers and quantity-constrained farmers responded most to changing interest rates and loan maturity conditions. In addition, unconstrained nonborrowers and risk-constrained farmers were statistically less sensitive to changes in credit conditions than unconstrained borrowers. This finding is significant because, as discussed, unconstrained nonborrowers represent 44% of our sample. Furthermore, risk-constrained farmers were the least sensitive to changes in interest rates and loan maturity across all other credit categories.

This study gives insights that can guide agribusiness policies to enhance access to credit in developing countries such as Chile. Agricultural credit capital institutions can better target their clientele by identifying farmers’ possible reactions before implementing policy changes to increase access to credit. This study’s credit constraint categorization and the results discussed can guide that identification. For instance, policies directed toward unconstrained borrowing farmers may find positive responses. However, implementing policies targeting the other three groups (unconstrained nonborrowing, risk-constrained and transaction cost-constrained farmers) is more challenging because these farmers are less responsive to changing credit conditions.

This article correlates farmers’ propensity to borrow and credit constraints across five categories of farmers. Prior research using this categorization framework has not identified farmers into the five groups. Furthermore, in addition to interest rate and loan maturity credit demand relative elasticity, this study adds the grace period elasticity, which has not been included in previous studies on agricultural credit.

This study aims to examine the price and income elasticities of short- and long-run industrial electricity demand in Brazil between 2003 and 2020. The research also examines the impacts of COVID-19 in Brazil’s industrial electricity sector, including an analysis in states more and less industrialized.

Dynamic adjustments models in panel data are used to present robust estimates and analyze the impact of different methodologies on reported elasticities.

The short-run price elasticity is estimated at −0.448, while the long-run values are around −1.60. Regarding income elasticity, the value is 0.069 in the short-run and is concentrated in 0.25 in the long-run. The inelastic results of income show that the industrial demand for electric energy follows the trend of loss of competitiveness of the Brazilian industry in the past years. In addition, the price of natural gas, the level of employment, and, in specific cases, the level of imports also influence industrial electricity demand.

The research is a pioneer in the investigation of the industrial behavior of electricity of the Brazilian industrial branch, using as control variables, the average temperature, and the level of rainfall, this one, so important for a country whose main source is hydroelectric. In addition, to the best of the authors’ knowledge, it is the first study, which is prepared to analyze the effects of COVID-19 on electric consumption in the industrial sector, investigating these impacts, including in the states considered more and less industrialized. The estimates generated may help in the design of the Brazilian energy policy.

How do informal lending institutions affect entrepreneurship? This paper aims to investigates the role of formal and informal credit market institutions in the decision to become an entrepreneur over the life cycle.

The author developed a dynamic Roy model in which a decision to become an entrepreneur depends on the access to formal and informal credit markets, nonpecuniary benefits of entrepreneurship, career-specific entry costs, prior work experience, education, unobserved abilities and other labor market opportunities (salaried employment and nonemployment). Using detailed Russian panel microdata (the Russia longitudinal monitoring survey) and estimating a structural model of labor market decisions and borrowing options, the author assesses the impact of the development of informal and formal credit institutions.

The expansion of traditional (formal) credit market institutions positively impacts all workers’ categories, reduces the share of entrepreneurs who borrow from informal sources and incentivizes low-type entrepreneurs to switch to salaried employment. The development of the informal credit market reduces the percentage of high-type entrepreneurs who borrow from formal sources. In the case of default, a higher value of the social network or higher costs of losing social ties demotivate low-type entrepreneurs to borrow from informal sources. The author highlights the practical implications of estimates by evaluating policies designed to promote entrepreneurship, such as subsidies and accessibility regulations in credit market institutions.

This study contributes to the literature in several ways. Unlike other studies that focus on individual characteristics in the selection for self-employment [Humphries (2017), Hincapíe (2020), Gendron-Carrier (2021), Dillon and Stanton (2017)], the paper models labor and borrowing decisions jointly. Previous studies discuss transitions between salaried employment and self-employment, taking into account entrepreneurial earnings, wealth, education and age, but do not consider the availability of financial institutions as a driving factor for the selection into self-employment. To the best of the author’s knowledge, this paper shows for the first time that the transition from salaried employment to self-employment is standard and consistent with changes in access to financial institutions. Another feature of this study is incorporating both types of credit markets – formal and informal. The survey by the European Central Bank on the Access to Finance of Enterprises (2018) shows 18% of small and medium enterprise in EU pointed funds from family or friends. Therefore, the exclusion from consideration of informal credit markets may distort the understanding of the role of the accessibility of credit markets.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

This paper seeks to explore the sensitivity of these parameters and their impact on fiscal policy outcomes. We use the existing literature to establish possible ranges for each parameter, and we examine how changes within these ranges can alter the outcomes of fiscal policy. In this way, we aim to highlight the importance of these parameters in the formulation and evaluation of fiscal policy.

The role of fiscal policy, its effects and multipliers continues to be a subject of intense debate in macroeconomics. Despite adopting a New Keynesian approach within a macroeconomic model, the reactions of macroeconomic variables to fiscal shocks can vary across different contexts and theoretical frameworks. This paper aims to investigate these diverse reactions by conducting a sensitivity analysis of parameters. Specifically, the study examines how key variables respond to fiscal shocks under different parameter settings. By analyzing the behavioral dynamics of these variables, this research contributes to the ongoing discussion on fiscal policy. The findings offer valuable insights to enrich the understanding of the complex relationship between fiscal shocks and macroeconomic outcomes, thus facilitating informed policy debates.

This paper aims to investigate key elements of New Keynesian Dynamic Stochastic General Equilibrium (DSGE) models. The focus is on the calibration of parameters and their impact on macroeconomic variables, such as output and inflation. The study also examines how different parameter settings affect the response of monetary policy to fiscal measures. In conclusion, this study has relied on theoretical exploration and a comprehensive review of existing literature. The parameters and their relationships have been analyzed within a robust theoretical framework, offering valuable insights for further research on how these factors influence model forecasts and inform policy recommendations derived from New Keynesian DSGE models. Moving forward, it is recommended that future work includes empirical analyses to test the reliability and effectiveness of parameter calibrations in real-world conditions. This will contribute to enhancing the accuracy and relevance of DSGE models for economic policy decision-making.

This study is motivated by the aim to provide a deeper understanding of the roles macroeconomic model parameters play concerning responses to expansionary fiscal policies and the subsequent reactions of monetary authorities. Comprehensive reviews that encompass this breadth of relationships within a single text are rare in the literature, making this work a valuable contribution to stimulating discussions on macroeconomic policies.

The network capacity deployed to manage the busy hour (or peak-hour) traffic remains underused during the nonbusy (off-peak) hours. Transferring some traffic from peak-hour to off-peak hours is likely to improve the utilization of network resources during the off-peak hours. This paper aims to examine whether diverting traffic from peak-hour to off-peak hours is possible by adopting the differential pricing policy.

The peak-load pricing theory suggests that the policy of differential pricing is socially optimal when there is peak demand for a particular duration and then there is off-peak demand. In this study, hourly traffic data from both peak and off-peak periods were collected from the Indian telecom service provider, “Aircel.” The paper analyzed the disparity in traffic between peak and off-peak hours using the nonparametric Tukey’s test. An experiment was also conducted to analyze whether a significant shift in telecom traffic occurs from the peak to the off-peak period when a price discount is applied during the off-peak period.

Statistically significant differences were observed in network traffic between peak-hour and off-peak hours. The network utilization of the telecom service provider Aircel was notably lower, particularly during the off-peak hours. The experiment demonstrated a high degree of price sensitivity among telecom service subscribers. Telecom Regulatory Authority of India (TRAI) has not considered network utilization of telecom service providers as a key performance indicator. Based on the outcomes of the study, this paper recommends that TRAI should adopt a more proactive approach by encouraging telecom service providers to follow the policy of differential pricing to enhance utilization of their network capacity.

To the best of the authors’ knowledge, this is the first paper to explore the issue of pricing as a tool for bringing about more uniform movement of telecom traffic, thereby enhancing network utilization within India’s telecommunications sector.

This study aims to investigate the effect of monetary policy transmission on the use-based classification of manufacturing industries in India, an integral aspect influencing the overall economic growth of the nation.

The empirical study applies a panel autoregressive distributed lag model to examine the relationship/association between monetary policy transmission mechanism and the output of manufacturing industries in the long run and short run.

In the long run, the findings reveal a negative association between money supply and manufacturing industries’ output, indicating that an increase in money supply corresponds to a decrease in manufacturing output. Conversely, a positive relationship is observed between manufacturing industries’ output and banks’ credit, indicating that an increase in bank credit leads to a corresponding increase in manufacturing output. In the short run, the results highlight a significant positive relationship between manufacturing output and monetary policy transmission variables, including money supply, statutory liquidity ratio, real exchange rate and foreign direct investment. The use-based classification of manufacturing industries such as primary goods, capital goods and intermediate goods exhibits greater responsiveness to monetary policy shocks than consumer durables and non-durables goods.

Policymakers are advised to regulate credit expansion to support the industry without risking financial instability, with key recommendations including stimulating consumer demand and adopting sector-specific policies to promote sustainable growth across diverse manufacturing sectors.

India, being a developing economy, efficient monetary policy transmission is crucial for boosting manufacturing output and employment. Nevertheless, there has been a scarcity of research concentrated on this pivotal intersection. This study aims to fill that gap, providing fresh insights into how monetary policy affects the growth of the manufacturing industry.

In the fashion of Martin (2012), we develop an innovative application to a standard, well-grounded methodology to investigate resilience in two critical dimensions: recovery and resistance. Our novel approach allows us to investigate the resilience performance to the 2008 financial crisis within countries of this macro-region according to their shock isolation and absorptive capacities.

By individually estimating six open economy DSGE models within the Central Europe and Baltic macro-region, we identify the business-cycle-volatility drivers for each country. Then, we use the outcome of our six estimates to conduct a principal component analysis to determine structural common characteristics required to explain economic resilience in the CEB macro-region.

In terms of resilience, Central European economies exhibit quite similar paths in terms of recovery, meaning they have similar economic structures. By contrast, Baltic countries behave differently, being outliers in opposite extreme positions. The contrary occurs for resistance: Baltic countries share a similar ranking, whereas Central European economies exhibit substantial differences.

It is important to acknowledge that a limitation of the analysis is that we explicitly consider each country as a stand-alone open economy which are subject to stochastic disturbances. Precisely, we do not model trade or other interactions across countries within the CEB region and with the rest of the world. Consequently, spillover effects in the aftermath of the shock are not accounted for.

We estimate the relative vulnerability or sensitivity of economies within the macro-region to disturbances and disruptions (resistance) and the speed and extent of recovery from such a disruption or recession (recovery). First, we built two different kinds of measures of resilience by aggregating the estimated parameters through non-centered and centered principal component analysis. Then, we use our model to investigate the relation between financial shock and the economic resilience across the region. The approach can be applied to several case studies, parsimoniously.

In 2016, the Chinese central government decentralized the responsibilities of housing market regulation to the municipal level. This paper aims to assess whether the decentralized market regulation is effective.

This study first investigates the fundamental drivers of urban housing prices in China. Taking into consideration the factors driving housing prices, the authors further investigate the effectiveness of decentralized housing market regulation by a pre- and post-policy comparison test using a panel data set of 35 major cities for the years from 2014 to 2019.

The results reveal heterogenous policy effects on housing price growth among cities with a one-year lag in effectiveness. With the decentralized housing market regulation, cities with fast price growth are incentivized to implement tightening measures, while cities with relatively low housing prices and slow price growth are more likely to do nothing or deregulate the markets. The findings indicate that the shift from a centralized housing market regulation to a decentralized one is more appropriate and effective for the individual cities.

Few policy evaluation studies have been done to examine the effects of decentralized housing market regulation on the performance of urban housing markets in China. The authors devise a methodology to conduct a policy evaluation that is important to inform public policy and decisions. This study helps enhance the understanding of the fundamental factors in China’s urban housing markets and the effectiveness of municipal government interventions.

This paper aims to examine the impacts of macroprudential policy on the shadow economy worldwide.

We compile a panel dataset covering 125 countries from 1990 to 2018. This paper mitigates potential endogeneity issues via two-stage least squares and the two-step generalized method of moments (GMM).

The robust results show that the overall tightening of macroprudential policies exerts an expansion impact on the shadow economy. Further examination of the 16 individual macroprudential policy instruments finds that loan restrictions, countercyclical buffers, surcharges for systemically important financial institutions and capital conservation buffers have positive and statistically significant effect on the shadow economy. This relationship is only present during tightening episodes of macroprudential policy as loosening episodes do not exhibit any significant impact. Finally, this paper documents the nonlinear effects of macroprudential policy.

The results suggest that the supervisory authorities may need to consider another parameter, which is the development of the shadow economy, when devising the optimal macroprudential policy responses.

To the best of the authors’ knowledge, this paper is likely the first to empirically document the impact of macroprudential policy on the shadow economy. It contributes to the growing literature on the potential side effects of macroprudential policy on the macro-economy.