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The main goal of this paper is to examine the evolution of Latin American productive integration in terms of the regional value added incorporated in intra-regional exports of Argentina, Brazil, Chile, Colombia, Mexico and Peru. In addition, the study traces the trade and productive integration trajectories for each of these countries from 1995 to 2015.

Based on the use of OECD’s global ICIO input-output tables, this paper applies the methodological framework by Wang et al. (2018) for the analysis of trade flows at the bilateral level, which allows breaking down the value of gross exports of each sector-country, depending on the origin of the value added contained in exports, as well as their use.

The estimates show very low shares of value added from regional partners in the intra-regional exports of the countries studied. Conversely, the weight of the value added incorporated in these exports by countries outside the region has increased in tandem with China’s expanding involvement in Latin America. This development, along with the downward trend in domestic value added incorporated in exports, indicates a lack of a regional integration process of any depth.

This article addresses an economic problem of conventional importance from a global value chain perspective using a novel methodology based on the use of global input–output tables.

This study examines the differences in the economic stimulus effects, transmission mechanisms, and output multipliers of government consumption, government traditional investment, and government science and technology investment.

This study constructs and estimates a New Keynesian model of endogenous technological progress embedded in the research and development (R&D) and technology transfer sectors. Using Chinese macroeconomic time series data from 1996 to 2019, this study calibrates and estimates the model and analyzes the impulse response function and a counterfactual simulation of expenditure structure adjustment.

The results show that compared with the traditional dynamic stochastic general equilibrium (DSGE) model, the endogenous process of technological progress amplifies the impact of government consumption shock and traditional government investment shock on the macroeconomy, leading to greater economic cycle fluctuations. As government investment in science and technology has positive external spillover effects on firm R&D activities and the application of innovation achievements, it can promote more sustainable economic growth than government consumption and traditional investment in the long run.

This study constructs an extended New Keynesian model with different types of government spending, which includes endogenous technological progress within the R&D and technology transfer sectors, thereby linking fiscal policy, business cycle fluctuations and long-term economic growth. This model can study the macroeconomic impact of fiscal expenditure structure adjustment when fiscal expansion is limited. In the Bayesian estimation of model parameters, this study not only uses macroeconomic variables but also adds a sequence of private R&D investment.

This study empirically examines the impact of some domestic as well as global factors such as trade openness (TO), money supply (MS), exchange rate, global oil prices (GOPs) and interest rate (IR) on inflation.

This study deploys a quantitative method considering 30 years of data (1991–2020) from four South Asian countries, namely, Sri Lanka, Pakistan, Bangladesh and India. To determine the potential impact of different factors on inflation, this study applies the panel analysis of the system generalized method of moments (SGMM).

This study empirically finds that TO, MS, exchange rate and GOPs have a positive impact on inflation, while IR and the structural adjustment program (SAP) have a negative impact on inflation. Out of the various determinants considered in this study, TO, exchange rate and the SAP are insignificant, while the rest of the variables are significant and consistent with previous studies.

This study informs policymakers about maintaining price stability and fostering economic growth in South Asian nations. It breaks new ground as the first empirical examination of the International Monetary Fund (IMF)’s SAP impact on inflation in the region.

This study tries to find out whether the SAP of the IMF is responsible for inflation in South Asian countries. It gives renewed attention to the causality of inflation from the perspective of countries receiving loans from donors, especially the IMF.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

The focus of this paper is to provide an assessment of the impact of imports from China on Indian manufacturing and capture the multifarious dimensions of India–China bilateral trade flows. By examining the comparative disadvantage imports (RCA<1), the paper critically examines their significance on India's industry output and performance and underlines factors beyond trade competitiveness.

For examining the impact of India's manufacturing imports from China on industry performance, four stages of analysis is adopted. First, the imports with RCA <1 have been identified. For these, BRCA was also computed. Second, trends in industry performance associated with high imports from China. Third, for estimating the impact of imports on industry output, augmented production function was specified and estimated with imports from China as a potential determinant. And fourth, comparison of industry performance between India and China.

The impact of imports from China on industry output is positive and significant. A 1% increase/decrease in the share of China in world imports will result in output increasing by 0.31%. The rise in imports from China seems to be on account of non-availability of necessary intermediate and capital goods domestically, thereby making these imports critical and complementary for production. This negates the threat perception of imports from China.

The paper recognizes the need for understanding the firm heterogeneity in import decisions and R&D intensity of imports. Across industries, the drivers for firms' decisions to import are “learning by importing’ and “self-selection” (Camino-Magro et al., 2020). Also, another important dimension at the firm-level analysis is the elasticity of substitution between foreign and domestic inputs. If the elasticity of substitution is low then high import barriers will lead to reduction of domestic output. These firm-level issues are important for effective policy interventions.

One, the inward looking focus of the industry which is exhibited in low export intensity will not provide the necessary impetus to propel the manufacturing sector to a higher technology frontier and translate the productivity gains to export competitiveness. Two, unless the domestic manufacturing is propelled from the current low/medium technology to high technology products, the current policy thrust on “self-reliance” cannot be realized.

Analysis is based on manufacturing imports with RCA<1 from China thereby underlining factors beyond trade competitiveness not covered by RCA methodology. Complementing the quantitative analysis with economic policy developments in China and India and contrasting the same has provided insights into the real factors determining India–China bilateral trade.

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 purpose of this paper is to investigate both the impact of different reward types and the adoption of knowledge-sharing practice on a crowdsourcing-based open innovation contest. Despite the benefit of knowledge sharing, contestants could struggle to find a balance between knowledge sharing and knowledge protection in open innovation.

The authors' approach follows a stylised contest model in a game-theoretical setting in which contestants first decide on their efforts and then the contest sponsor chooses the winner. Moreover, the outcome of an open innovation contest is delineated as either intermediate goods that require further refinement and risk-taking versus a market-ready end product for the contest sponsor. The authors also investigate how knowledge sharing among contestants would be influenced by reward types such as fixed-monetary prizes vs performance-contingent awards.

The contest sponsor will lower the prize level after adopting knowledge sharing. Therefore, the total effort will decline regardless of the reward type. Moreover, the choice of reward types depends on the contest sponsor's characteristics because the performance-contingent award is suitable for a large market size but the fixed-monetary prize can more efficiently raise the quantity of contestant inputs.

Prior studies have tested the connection between contest performance and knowledge sharing in crowdsourcing-based contests; however, there is not an integrated framework to best design the operation of a contest when considering different reward types and knowledge-sharing practices.

Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors investigate the role of EEs in supporting global value chain (GVC) activities.

The authors employ the fuzzy-set qualitative comparative analysis (fsQCA) technique to identify practical configurations of EE’s framework and systemic conditions spurring GVC activities in 80 countries.

The findings suggest different configurations of EE`s framework and systemic conditions necessary for various GVC activities regarding input-output structure, geographical scope, upgrading, and forward and backward participation.

This study contributes to the extant literature by pioneering the EE approach to explaining GVC development. Moreover, the findings provide novel insights for understanding the EE – GVC interplay. As a result, the study offers a more nuanced understanding of how the EE supports GVC activities.

The study evaluates the effects of GVC participation on firm productivity and profitability. Hence this study aims to find evidence whether there is a clear difference between the productivity and profitability effects of simple and complex backward and forward participations for Turkish firms.

The authors employ a firm level data from the Türkiye's both first and second top 500 industrial enterprises from 1993 to 2019. In addition, the authors calculate country-sector level both backward and forward GVC participation indices with their simple and complex sub-indices for each year from 1990 to 2015 from the Full Eora data of the Eora Global Supply Chain Database. The authors estimate the model with OLS and fixed effects. To understand the role of the 2008 global crisis, the authors also undertake estimations for the pre-crisis and post-crisis. The authors also divide the data by R&D intensity of sectors.

While backward GVC participation lowers both labor productivity and profitability growth, forward GVC participation promotes both. Moreover, simple and complex backward participation have similarly negative effects on productivity and profitability growth, simple and complex forward participation have the completely opposite effects though. The authors then provide substantial evidence for the differing effects of participation on productivity and profitability growth between pre-crisis and post-crisis periods. Interestingly, backward participation has a negative impact for both hi-tech and low-tech firms while forward participation boosts the productivity growth only for low-tech firms, probably due to the relatively more upstream position of low-tech firms.

To the best of the knowledge, no previous study has yet examined the profitability effects of GVC for firms. Second, in addition to overall backward and forward GVC participation rates, the authors also calculate and utilize simple and complex GVC measures in the estimations. Third, to reveal whether the global financial crisis leads to a shift in the productivity and profitability effects of GVCs, the authors separately run the regressions for the pre- and post-crisis periods. Fourth, the authors then investigate the argument that hi-tech sectors/firms could benefit more from joining GVCs compared to firms in low-tech technology sectors.