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This study estimated total import demand elasticities concerning income, import prices and domestic prices. A high propensity to import constitutes a significant obstacle to economic growth in Mexico since the benefits of increased exports or any other aggregate demand expansion leak to the rest of the world.

This paper estimated a Vector Error Correction Model of the total import demand elasticities concerning income, import prices and domestic prices. Total imports are a dependent variable, while Gross Domestic Product (GDP) and import and domestic prices are the independent variables.

The principal finding is that an increase of 1 peso in the Mexican GDP leads to a rise of 0.50 pesos in Mexican imports; the elasticity of import demand for prices is low. Still, the elasticity of import demand for domestic prices is 2.14 times greater than that for import prices. These results have significant economic policy implications, such as promoting the expansion of the domestic market and the national content of exports.

It is tempting to estimate the import demand function for the entire 1993–2019 period since such data is available. But by doing so, the authors would overestimate the propensity to import, given that from 1993 to 2019, the proportion of imports as a percentage of GDP went from 11.37 in 1993 to 29.66 in 2019. Therefore, it makes more sense to estimate the import demand function from 2000 to 2019, a period with a stable proportion of imports to GDP.

A high level of imports in developing countries means that much of their aggregate demand is filtered abroad. Therefore, the low impact of its exports on GDP is related to the Mexican economy’s high imports. The authors calculate this relationship with new data and methods.

Despite being a flexible tool that can address several macroeconomic issues, Dynamic Stochastic General Equilibrium (DSGE) models have been rarely used to analyse the interaction between monetary and fiscal policy until the post-financial crisis, leaving a gap in the analysis of how government consumption affects the transmission mechanism of monetary policy. This motivates this paper to analyse how government consumption affects the dynamics of a small open economy, once the former is included in a non-separable form to the utility function. To the best of the authors' knowledge, this issue has not been addressed by the literature, and the authors aim to do so in this paper.

A standard New Keynesian model for a small open economy is used to allow for the presence of non-separable government consumption in the utility function. The model is supported by panel regressions.

The inclusion of Government consumption dampens the transmission mechanism of monetary policy. The degree of openness dampens the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it. Empirical estimates for 35 OECD countries support the theoretical findings of the model.

The effect of government consumption on the transmission mechanism of MP has not been addressed in the literature. This paper contributes to the literature by addressing this issue.

• • The inclusion of Government consumption dampens the transmission mechanism of monetary policy.

• • The degree of openness alleviates the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it.

• • Empirical estimates for 35 OECD countries support the theoretical findings of the model.

• The inclusion of Government consumption dampens the transmission mechanism of monetary policy.

• The degree of openness alleviates the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it.

• Empirical estimates for 35 OECD countries support the theoretical findings of the model.

The purpose of this study is to use the structural model to determine the influence of mobile telecommunication on Egypt’s economic growth from 2000 to 2009. By focusing on mobile unique subscribers and mobile broadband-capable device penetration as indicators of telecommunications adoption, the authors seek to understand their overarching effects on the nation’s economic landscape.

The paper uses quarterly time-series data set over the period 2000–2019 and uses a structural econometric model based on an aggregate production function, a demand function, a supply function and an infrastructure function to detect causality and examine long-run relationships between variables.

The findings of the structural model reveal that both mobile unique subscribers and mobile broadband-capable device penetration significantly contributed to Egypt’s gross domestic product (GDP) growth from 2000 to 2019. Specifically, a 1% increase in mobile unique subscriber penetration and mobile broadband-capable device adoption is estimated to result in an average annual contribution to GDP growth of 0.172% and 0.016%, respectively.

The scarcity of panel data is the main research limitation for comparative study with other Middle East and North African Region (MENA) countries. Research extensions would include testing the significance of complementarities such as improving governance measures and building human capacity for both households and firms, which are necessary to boost the impact of telecommunication on economic growth in the MENA region.

Based on these findings, the study puts forth policy recommendations aimed at maximizing investment in network utilization, including mobile and internet services, as well as fixed broadband subscriptions. It highlights the crucial role of these investments in promoting social and economic development, not only in Egypt but also across the MENA region as a whole.

The findings of this research emphasize the importance of strategic investments in network utilization, encompassing mobile, internet services and fixed broadband subscriptions. Such investments are pivotal for fostering social and financial inclusion. The study underscores the potential of these investments to drive social and economic progress, not just within Egypt but throughout the entire MENA region.

Overall, existing literature generally supports the notion that the telecommunications sector has a positive economic impact. However, there is a gap in the literature when it comes to understanding the specific effects of the Egyptian telecommunications sector on the country’s economy, particularly in relation to the Egypt Vision 2030. The study aims to fill this gap by focusing specifically on Egypt and providing additional insights into the direct and indirect effects of the Egyptian telecommunications sector on the economy. By conducting a thorough analysis of the sector’s role, the authors aim to contribute to the existing literature by providing context-specific findings and recommendations.

The purpose of this research is to provide a theoretical and practical theory and application that provides understanding and means to manage complex infrastructures.

In this research, complexity, nonlinear, noncontinuous effects and aleatoric and data unknowns are bypassed by directly addressing systems' responses. Graph theory, statistics and digital signal processing (DSP) tools are applied within a theoretical framework of the theory of faults (ToF). Motivational complex infrastructure systems (CISs) are difficult to model. Data are often missing or erroneous, changes are not well documented and processes are not well understood. On top of it, under complexity, stalwart analytical tools have limited predictive power. The aleatoric risk, such as rain and risk cascading from interconnected infrastructures, is unpredictable. Mitigation, response and recovery efforts are adversely affected.

The theory and application are presented and demonstrated by a step-by-step development of an application to a municipal drainage system. A database of faults is analyzed to produce system statistics, spatio-temporal morphology, behavior and traits. The gained understanding is compared to the physical system's design and to its modus operandi. Implications for design and maintenance are inferred; DSP tools to manage the system in real time are developed.

Sociological systems are interest driven. Some events are intentionally created and directed to the benefit and detriment of the opposing parties in a project. Those events may be explained and possibly predicted by understanding power plays, not power functions. For those events, sociological game theories provide better explanatory value than mathematical gain theories.

The theory provides a thematic network for modeling and resolving aleatoric uncertainty in engineering and sociological systems. The framework may be elaborated to fields such as energy, healthcare and critical infrastructure.

ToF provides a framework for the modeling and prediction of faults generated by inherent aleatoric uncertainties in social and technological systems. Therefore, the framework and theory lay the basis for automated monitoring and control of aleatoric uncertainties such as mechanical failures and human errors and the development of mitigation systems.

The contribution of this research is in the provision of an explicatory theory and a management paradigm for complex systems. This theory is applicable to a wide variety of fields from facilities and construction project management to maintenance and from academic studies to commercial use.

The paper aims to introduce a novel concept to solve the bi-level multi-criteria nonlinear fractional programming (BL-MCNFP) problems. Bi-level programming problem (BLPP) is rigorously flourished and studied by several researchers, which deals with decentralized decisions by comprising a sequence of two optimization problems, namely upper and lower-level problems. However, on the other hand, many real-world decision-making problems involve multiple objectives with fraction aspects, called fractional programming problems that reflect technical and economic performance.

This paper introduces a VIKOR (“VlseKriterijumska Optimizacija I Kompromisno Resenje”) approach to solve the BL-MCNFP problem. In this approach, an aggregating function based on L_P metrics is formulated on the basis of the “closeness” scheme from the “ideal” solution. The three steps perform the solution process: First, a new concept is attempted to minimize and maximize of the numerators and denominators from their respective ideal solutions and anti-ideal values simultaneously. Second, for each level, the K-dimensional objective space of each level is converted to a one-dimensional space by an aggregating function. Third, to obtain the final solution, all levels are combined into single-level model where the decision variables of upper levels are interrelated with other levels through fuzzy strategy-based linear and nonlinear membership functions.

The effectiveness of the proposed VIKOR is demonstrated by numerical examples, where the reported results affirm that the extended VIKOR method provides superior results in comparison with the same methods in the literature, and it is a good alternative to BL-MCNFP problems.

In terms of the assistance-based right decision, a parametric analysis for the weight of the majority is provided to exhibit a wide range of compromise solutions for the decision-maker.

The purpose of this study is to explore the link between aggregate production efficiency and the extent of linguistic clustering in Indonesia.

The author draws on the stochastic frontier model and applies it to the data on Indonesian provinces to compute the effects of various determinants on these provinces' aggregate production efficiency. The key determinant is the spatial index of linguistic clustering that the author believes has never been applied before in this context.

Linguistic clustering is an important determinant of aggregate production efficiency. Linguistic diversity is positively associated with productive efficiency if members of a specific linguistic group are not clustered beyond a certain level.

To the best of the author’s knowledge, this is the first study that links the spatial index of linguistic clustering (because of Massey and Danton) to production efficiency. In other words, the contribution of this study is to introduce a geographical dimension to the mainstream analysis of the association between ethnic diversity and economic performance.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

Transient climate sensitivity relates total climate forcings from anthropogenic and other sources to surface temperature. Global transient climate sensitivity is well studied, as are the related concepts of equilibrium climate sensitivity (ECS) and transient climate response (TCR), but spatially disaggregated local climate sensitivity (LCS) is less so. An energy balance model (EBM) and an easily implemented semiparametric statistical approach are proposed to estimate LCS using the historical record and to assess its contribution to global transient climate sensitivity. Results suggest that areas dominated by ocean tend to import energy, they are relatively more sensitive to forcings, but they warm more slowly than areas dominated by land. Economic implications are discussed.

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.