Search results

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.

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 aims to explore the construction of a valid and reliable measure for the competitiveness of cities that excludes the drivers of competitiveness from the index construction. Not incorporating these drivers in the index avoids the problem of assuming relative contributions (i.e. weights) of these drivers on competitiveness as a maintained hypothesis.

From the definition that competitiveness is the ability of a city to sustain prosperity, this study derives a model called the hedonic well-being index (HWI) in which prosperity is measured by using the consumption of goods and service including leisure. This study then uses secondary data sources to construct an exploratory HWI (assuming a Cobb Douglas functional form) and compare this index to three benchmarks, namely, income, gross domestic product (GDP) per capita and the World Happiness Report (WHR) index. This study also review the component expenditure of the index across geographical locations.

The HWI is better predicted by the WHR index (a subjective well-being index) than by the GDP per capita (a measure of output), owing to the inclusion of leisure and household production absent in per capita GDP. This study explored and found regional variations in the distribution of the expenditure components in the HWI.

This paper demonstrates the feasibility of constructing an exploratory HWI to measure the competitiveness of cities using secondary data. The reliability of the index can be improved using primary data in future research. Separating the drivers from the definition of competitiveness allows testing of the contribution and interaction of these drivers on competitiveness.

This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.

The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.

The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.

Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

Our study aims to evaluate the impact of infrastructure and public investment on private investment in machinery and equipment in Brazil from 1947 to 2017. The contribution of our article to the existing literature lies in providing a more comprehensive understanding of the presence or absence of the crowding effect in the Brazilian economy by leveraging an extensive historical database. Our central argument posits that the recent decline in private capital accumulation over the last few decades can be attributed to shifts in economic policies – moving from a developmentalist orientation to nondevelopmental guidance since the early 1990s, which is reflected in the diminished levels of public investment and infrastructure since the 1980s.

We conducted a series of econometric regressions utilizing the autoregressive distributed lag (ARDL) model as our chosen econometric methodology.

Employing two different variables to measure public investment and infrastructure, our results – robust across various specifications – have substantiated the existence of a crowding-in effect in Brazil over the examined period. Thus, we have empirical evidence indicating that the state has influenced private capital accumulation in the Brazilian economy over the past decades.

Our article contributes to the existing literature by offering a more comprehensive understanding of the crowding effect in the Brazilian economy, utilizing an extensive historical database.

Financial inclusion is a critical component of financial development, which disseminates accessible financial services to benefit all parts of society and consequently promotes economic growth. The study explores the dynamic common correlated effects of financial inclusion on economic growth in Organization of Islamic Cooperation (OIC) countries.

The conventional econometric techniques overlook heterogeneity and cross-sectional dependence and provide false results. Hence, a unique methodology, ‘Dynamic Common Correlated Effects (DCCE)’, is used, which can efficiently tackle the above-mentioned issues.

The DCCE estimation indicates a positive and significant impact of financial inclusion on economic growth in overall and higher-income OIC economies. Moreover, in the lower-income OIC group, financial inclusion is inversely correlated with economic growth, which converts into a positive linkage by including an interaction term of financial inclusion and institutional quality.

Based on the research outcomes, it is recommended that policymakers and governments of OIC economies seek to increase financial inclusion to achieve sustainable, optimal and inclusive economic growth.

The DCCE technique in this study considers heterogeneity and cross-sectional dependence among countries and thus provides robust findings.

The main purpose of this study is to examine the impact of imported inputs on firms' productivity in selected South Asian economies, namely Pakistan, India and Bangladesh. Furthermore, this study explores the complementarity between firms' capabilities and imported inputs in an augmented productivity framework.

A dataset comprising 7117 manufacturing firms of selected South Asian economies was taken from the World Bank for 2013 and 2014. The empirical analysis was based on stochastic frontier models, the ordinary least square method and instrumental variable estimation techniques.

The empirical results show that imported inputs have positive and significant effects on the firms' productivity in the selected countries. Moreover, the study findings demonstrate that firms' capabilities play a complementary role in expanding the firms' production frontier.

The study outcomes suggest that reducing tariffs on imported inputs will enhance the firms' productivity in the selected emerging economies. However, the study further finds that the potential gain of imported inputs is conditional on the firm's capabilities. It implies that firms operating in these countries can improve their performance by allocating more resources to capabilities, such as workers’ training, management and internal R&D effort.

The existing literature on the subject is sceptical about the positive impact of imported inputs on firms' productivity in the case of developing countries. In this regard, the shortage of skilled labour and firms' capabilities are compelling rationales that need to be explored. Thus, the potential contribution of the study lies in explaining the moderating role of firm's capabilities operating in the selected emerging economies in the nexus of imported inputs and productivity.

The purpose of this paper is to show that forgotten classics, such as Melvin T. Copeland’s (1924) Principles of Merchandising, can still teach lessons to students of the history of marketing thought.

The method involved using various key words on several internet search engines. The extensive internet search produced more than a dozen contemporaneous reviews and commentaries. Additionally, there was an intensive search through the histories of marketing thought literature. The extensive and intensive searches allowed a meta-analysis reexamining Copeland’s principles in light of future historical developments from the mid-1920s to the 21st century.

Historically, Copeland’s principles established the commodity school of marketing thought. (One of the three traditional approaches to understanding marketing taught to generations of students from the mid-1920s until the mid-1960s.) Although the traditional approaches/schools have long gone out of favor, Copeland’s classification of consumer and industrial (business) goods (products and services) have stood the test of time and are still in use 100 years later. Long overlooked, Copeland’s (1924) Principles of Merchandising also anticipated the marketing management/strategy as well as the consumer/buyer behavior schools of marketing thought, dominant in the discipline since the 1960s, for which he has seldom – if ever – been acknowledged.

Historical research is limited because some relevant source material may no longer exist or may have been overlooked.

There have been no reviews of Copeland’s principles in almost a century, and no published meta-analysis of this forgotten classic exists. New discoveries reveal the value in studying marketing history and the history of marketing thought. For marketing as a social science to progress, it is invaluable to understand how ideas originated, were improved and integrated into larger conceptualizations, classification schema and theories over time.

Firms are the primary producers of innovations, and understanding how these agents acquire, update and manage the knowledge of their employees is central to understanding economic growth. However, in developing economies, technology adaptation plays a critical role in innovation compared to knowledge creation. Thus, this research investigates the role of human capital in innovation at the firm level in the case of a small developing economy, which ranks highly on several human capital dimensions but shows declining levels of investment in advanced human capital development in its manufacturing sector.

This research examines the relationship between innovation and human capital at the firm level in a small peripheral economy. The human capital theory is applied to a firm context to understand variations in innovative behavior depending on the size of manufacturing companies. The effect of several human capital dimensions on product innovation is estimated by applying binomial logistic regression models with firm and time-fixed effects.

This article contributes to innovation economics and public policy by highlighting that not all dimensions of human capital operate similarly for all companies in the context of developing economies. In such settings, technology adaptation plays a critical role in innovation. While employees' human capital endowments significantly impact small firms in that context, firm-level practices such as internal training are crucial for large companies. Consequently, policymakers should consider that firms' human capital endowments impact their innovative behavior differently to avoid one-size-fits-all policy design approaches in this regard.

Prior research on the relationship between human capital and innovation in developing economies was based on a cross-sectional approach. This research's unique panel dataset covering 11-year triennial innovation surveys enabled a modeling strategy that controls for time-invariant unobservable firm characteristics. Three aspects of firms' human capital have been analyzed human capital endowments, internal training and human resource management (HRM) practices for the first time longitudinally in a developing economy, enabling to contrast of empirical findings with policy design.

The purpose of this paper is to challenge the older perspective on the nature of workplace politics and its disruptive role in organizations. In particular, this paper references the positive aspect of meaningful relationship building that is promoted by workplace politics and how the very politicking becomes a necessary tool for generating and maintaining social capital within the organizational boundaries.

The paper relies on presenting author’s viewpoint on positive workplace politics and its intertwined relationship with social capital.

In the process of politicking, the relationships built, the networks established and maintained and the social capital acquired are of immense value. To thwart the negative effects of organizational politics such as disengagement from work, intentions to quit, low job satisfaction, etc., we must look into the multidimensional nature of politics and the value that social capital adds to it.

The positive side of politics has long been in the shadows of its pronounced negative side. The paper presents the ground work for exploring the many colours of organizational politics and also delve into the factors that can thwart the negative effects of politics that may be experienced by the employees.

The paper contends that workplace politics is not just responsible for the disruptive and unwanted behaviours but is rather an important source of the positive and productive interpersonal relationships that are often useful in accomplishing individual and organizational goals.