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The purpose of this study to examine the effect of financial constraint on intangible investment because intangible investment provides an overall picture of marketing investment and activity. Intangible investment also plays a significant role in facilitating future sales. Using a new measure of intangible investment (Peters and Taylor, 2017), the authors first establish that intangible investment is positively related with future sales. Then, using a new text-based measure of financial constraint, the authors show that financial constraint has a significant negative effect on future intangible investments after controlling for other factors. Intangible investment has three components. The first is R&D, the second is 30 per cent of selling and general administrative expense (SGA) and the third is other intangibles. The authors find that the negative and significant effect of financial constraint on 30 per cent SGA is stronger. This indicates that financially constrained firms reduce marketing related investments. The authors then considered firm size and found that smaller firms facing financial constraint continue to increase their intangible investments, whereas larger firms reduce their intangible investment. As a robustness test, the authors use advertising expenditure as a measure of promotion related investment and find that financial constraint has a negative effect on advertising spending. The authors then use two traditional measures of financial constraint in their analysis to compare with the new text-based measure.

The authors use ordinary least squares with cluster robust standard error to conduct their empirical analysis.

First the authors establish that intangible investment positively affects future sales. Further the authors find that financial constraint negatively affects intangible investment. Moreover, financial constraint negatively affects the brand capital of intangible investment.

The authors did not conduct any industry specific analysis to see how financial constraints affect intangible investment across different industries. Industry specific analysis is important because in some industries/sectors intangibles are clearly more important than in others, so this is an important avenue for future research. It will also be interesting to explore if and how financial constraint has a mediating effect on sales growth via intangible investment and different components of intangibles.

This study identifies another important factor that can negatively affect brand capital investment.

The authors have used a measure of financial constraint and text mined all the annual reports of US firms for the period of 1994-2016 to compute this measure.

The purpose of this paper is to examine the monetary policy transmission mechanism for the Fiji Islands using a structural vector autoregressive (SVAR) model for the period 1975 to 2005.

The SVAR model investigates how a monetary policy shock – defined as a temporary and exogenous rise in the short‐term interest rate – affects real and nominal macro variables; namely real output, prices, exchange rates, and money supply.

The results suggest that a monetary policy shock statistically significantly reduces output initially, but then output is able to recover to its pre‐shock level. A monetary policy shock generates inflationary pressure, leads to an appreciation of the Fijian currency and reduces the demand for money. The paper also analysed the impact of a nominal effective exchange rate (NEER) shock (an appreciation) on real output and found that it leads to a statistically significant negative effect on real output.

The findings of this study should be of direct relevance to the research and policy work undertaken at the Reserve Bank of Fiji.

For a small economy, such as Fiji, where monetary policy is key to sustainable macroeconomic management, this is the first paper that undertakes a dynamic analysis of monetary policy transmission. The paper uses time series data over three decades and builds a structural VAR model, rooted in theory. This paper will be of direct relevance to the Reserve Bank of Fiji. The approach and model proposed will also be useful for applied monetary policy researchers in other developing countries where inflation rate targeting is a key element of the monetary policy setting.

The purpose of this paper is to examine the convergence analysis of public debt among Indian states using annual data from 1990‒1991 to 2014‒2015.

The paper tests this hypothesis using club convergence technique propounded by Phillips and Sul (2007).

The results reveal the existence of debt divergence for overall Indian states. States are formed into four clubs on the basis of their level of debt, and three clubs support the hypothesis of club convergence. Further, the total public debt decomposes into three compositions such as market loans, bank loans and loans and advances from the central government. The existence of convergence is found for market loans and bank loans; however, the presence of divergence is found in case of loans and advances for overall states.

Since public debt plays an important role for fiscal health of the Indian states, findings of this study suggest to squeeze the fiscal consolidation further for Indian states whose debts as a percentage to gross state domestic product are on the higher side. Further, the examination of debt convergence helps to manage debt level among the states because heavy dependence on public debt could retard investment and economic growth.

Whereas bulk of empirical studies emphasize on examining the linkage between public debt and economic growth, and issue on debt sustainability across Indian states, examination of convergence of debt and its compositions (markets borrowings, bank loans and loans and advances from the central government) among the Indian states is scanty.

There is vast disparity in public expenditure on science, technology and environment (STE) across various Indian states. Public expenditure on STE is crucial in maintaining symmetric growth, social cohesion and sustainable development. Literature on this topic is scarce, which prompted the investigation of club convergence of STE public expenditure. In particular, the purpose of this paper to study the club convergence of STE public expenditure in the case of 20 Indian states during the period from 1987–1988 to 2019–2020.

This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables identification of multiple steady states or club convergence, unlike beta and sigma convergences.

The findings of this paper show that all Indian states do not converge towards single steady states. This suggests a disparity in STE public expenditure across Indian states. Moreover, the findings favour three clubs that have their own unique transition paths. The results of this study are supported by the robustness check.

The findings suggest that the allocation of public expenditure on STE can be made based on club convergence to achieve social cohesion, sustainable development and millennium development goals across states.

Although several previous studies have investigated the convergence of public expenditure by considering either aggregate public expenditure or health/education expenditure, literature on the convergence hypothesis of STE public expenditure, particularly across Indian states, is scarce. Moreover, this paper is unique, as it examines multiple steady states or club convergence. Finally, this paper contributes to policymaking by suggesting which states should be given a push to achieve social cohesion and sustainable development.

Food loss and wastage is an issue of global concern and the household sector is one of the biggest contributors to this. Solar drying has been explored by many eminent researchers as a solution to this problem but there have been concerns about the lack in designs, higher cost, lower performance, and consumer acceptability. The present research aims to design a small-scale domestic solar dryer by using computer software.

Response surface methodology (RSM) and computational fluid dynamics (CFD) are used to design the domestic solar dryer. Initially, design variables (inlet and outlet vent height) are identified and a design of experiments has been created using RSM for set of experimental runs. The experimental runs suggested by RSM were carried out using CFD simulation in COMSOL Multiphysics software and the results were used for optimization of response variables (outlet velocity and drying chamber temperature) in RSM.

Outlet vent height was found to be most significantly affecting parameter to both the responses. The optimum values of inlet and outlet vent heights were 0.5 and 2.5 cm, respectively with the overall desirability of 0.728. The model accuracy was tested by conducting a confirmation test as post processing in design expert software.

Designing a solar dryer is a complex, costly and time consuming process, this study presents an easy, economic and fast method to design a new solar dryer. It would help researchers to design and develop new domestic as well as large size industrial solar dryer.