Institutional framework and economic development: international evidence

This paper examines the effect of ‘quality’ of the institutional framework on economic development. Our empirical results support the hypothesis that ‘good’ institutions improve efficiency and accelerate growth. The positive effect of institutional ‘quality’ is more pronounced with mutually reinforcing support of economic freedom. Our results also indicate that ‘good’ institutions help developing countries grow faster to achieve conditional convergence. We infer from the results that economic development requires not only physical and human capital formation, but also freedom to choose and institutional support.     

Incorporating daily market uncertainty data into a conventional short-run dynamic model: the case of the black-market exchange rate in Iran

The effect of market uncertainty on a country’s currency, while widely recognized, is either omitted from mainstream models or addressed using low-frequency series, which are typically subject to aggregation bias and substantial lags. In this article, we propose a new mixed-data sampling (MIDAS) modelling framework that enables us to incorporate the asymmetric daily effects of market uncertainty in a conventional monthly error correction model. We achieve this by proxying market uncertainty via the value of a ‘safe haven’ asset (gold) that investors reallocate towards in the face of heightened market risk. We apply the model to the Iranian black-market exchange rate, using a mix of the daily price of gold (28 June 2010–19 August 2018) and monthly data (July 2010-July 2018) on relative prices. Our results indicate that purchasing power parity (PPP) holds despite the recent unprecedented depreciations in the Iranian currency arising from several rounds of international sanctions. We also find that increased uncertainty can lead to instantaneous and substantial depreciations, whereas stabilization back towards the PPP path is much more sluggish.     

The relevance of pecking order hypothesis for the financing of computer software and biotechnology small firms: some UK evidence

This study explores the funding issues at the early stages of development of computer software and biotechnology small firms in the UK. This study reviewed previous relevant literature in this area and presents empirical evidence derived from an extensive online questionnaire survey. The sample contains a total of 83 small firms, which includes 41 biotechnology and 42 software firms. With regards to funding issues, we found that software firms reports more funding problems than the biotechnology firms. Software firms are fastest growing firms and goes through the early stages of development quicker than the biotechnology firms. With regards to the sources of funding the evidence shows that biotechnology small firms mainly use venture capital finance whilst the main source of funding for the software firms are personal savings and house mortgage/re-mortgage. On the one hand, software firms seem to follow the pecking order hypothesis whilst financing their business growth and development. On the other hand, the pecking order hypothesis may not be fully followed by the biotechnology small firms. However, both software and biotechnology small firms report difficulties in securing equity finance. Software firms are financially constrained not only due to the supply side financial constraints but also by the demand side financial constraints.     

Crash-related factors associated with the severity of road traffic injuries in Iran

Although the impact of traffic crashes is very high in Iran, there are few works on the association of crash-related factors with injury severity. This study was conducted on 145 drivers injured on the Qazvin-Loshan road in order to assess this association. The New Injury Severity Score (NISS), based on the conditions of the injured drivers during their first visit to regional hospitals, was used as the main outcome measure. Multiple linear regression analysis was performed by considering logarithmic scale for NISS as response variable and adjusting for the confounding effects, including the transfer to hospital variables. The results showed that high-vehicle damage (i.e. damage with repair cost more than 25% of the pre-crash value of the driver's vehicle) and being trapped inside the motor vehicle raised the NISS by 5.25 (95% confidence interval (CI) 2.51-10.71) and 2.34 (95% CI 1.20-4.67), respectively.     

An empirical analysis of the US stock market and output growth volatility spillover effects on three Anglo-Saxon countries

This paper examines the dynamic and switching effects of volatility spillovers arising from US stock market returns and GDP growth on those of Australia, Canada and the UK. For this purpose, we use quarterly data (1961q1–2013q1) and a constant probability Markov regime switching model. We found that the US stock market volatility significantly affects the stock market volatility of all three countries at least in one of the two specified regimes over time. However, the stock market volatilities in none of the three countries are contemporaneously influenced by the US output volatility even after allowing for two distinct regimes. On the other hand, the US stock market volatility exerts significant influences on the output volatilities of both Australia and the UK. Compared with Australia and the UK, Canada and the US show substantial output volatility co-movements, thereby confirming the close association between the two neighbouring economies through the NAFTA (North American Free Trade Agreement). We conclude that shocks emanating from the US stock market have unequivocal flow-on effects on the output and return volatilities of the other economies.     

On the need for national land administration infrastructures

Many nations lack a coherent national approach to land administration. Instead, land information and processes are frequently disaggregated across states, provinces, cantons, counties, or municipalities. This is particularly the case in federated countries. The growing body of land administration theory often assumes or prescribes the need for national systems; however, the justification for this approach requires further explanation. Without justification, nations that maintain disaggregated systems lack the impetus to unlock the opportunities veiled within their disparate land administration systems. Moreover, a nation's ability to respond effectively to emerging national and global-scale issues such as climate-change is greatly impeded. This paper aims to explain the need for national land administration infrastructures. Qualitative case studies of the Australian context and the method of triangulation inform the justification. The research reveals most drivers can be classified into six overarching subsets: adherence to international standards by national governments, better federal or central governance, improved shared governance, scale of economies for lower levels of government, opportunities and savings for business, and social inclusion for citizens. Unfortunately, specific drivers are found to be complex and changeable, as political, scientific and environmental debates raise policy issues: there is no single solution. As an alternative, nations must seize on the specific drivers relevant to their context. They must employ them to transform disparate land administration systems into multi-purpose national land administration infrastructures that deliver benefits to all stakeholder groups.     

Refitting the Kuznets curve using a gender-specific threshold model

Previous studies have reached mixed conclusions regarding the relationship between inequality and per capita income. These studies, however, fail to consider gender differences in income inequality and how these may impact on the relationship between income inequality and per capita income. Using Australian taxation statistics, we derive three sets of Gini coefficients (i.e. female, male and total) for the period 1950–2013. We then examine the relationship between inequality and real per capita income and find that a gender-specific threshold panel regression outperforms three other conventional models. Our findings suggest that ‘one set of coefficients does not fit all’ in that the use of aggregate and constant coefficients may mask variations within, and between, gender inequality over time.     

An index for cross-country analysis of ICT infrastructure and access

The purpose of the present article is to devise an index for measuring and analyzing the divide among countries in the area of information and communication technology (ICT) infrastructure and access. Understanding the fact that there are many factors influencing the digital divide, this research is not intended to measure the digital divide in terms of different inequalities, but it rather attempts to take only one of the most important of these factors (maybe the most important of them) into consideration for measuring and analyzing divide between countries, that is, ICT infrastructure and access. In contrast to the majority of the indices in this context, the proposed index is built upon defining and conceptualizing ICT infrastructure and access. In addition, the index uses core ICT indicators on which the international community and experienced modelers have consensus that they measure the information society suitably. Therefore, the index can be exploited as the basis and standard for internationally comparable statistics in ICT infrastructure and access area. Moreover, it is the second index based on core ICT indicators after the Digital Opportunity Index (DOI) that was developed by the International Telecommunication Union (ITU) in 2005. However, in the current article, using Data Mining methods, Markov Chain Monte Carlo (MCMC) (to impute missing data) and Multi-Stage Factor Analysis (FA) (for aggregating the indicators), many problems and limits of the existing indices, the DOI in particular, such as the lack of data for analyzing ICT infrastructure and access, use of equal weighting or experts’ opinions to aggregate the indicators, are avoided. Since this index is developed by statistical procedures, it is flexible, adaptable, and modifiable over time while it sustains its original structure. It is comprised of two main dimensions: ‘ICT access’ and ‘coverage of mobile and access tariffs’ and 10 indicators. Finally, comparing the proposed index with the other indices in this field and gross national income (GNI) per capita of 150 countries, this index is tested; then, it is utilized to measure and analyze the divide between countries in the two dimensions, different geographical areas, economic conditions, and levels of ICT infrastructure and access.     

Determinants of Credit Constraints: Evidence from Sindh,Pakistan

This article investigates the determinants of credit constraints: evidence from Sindh, Pakistan. Cross-sectional farm-level data is collected during November and December 2016. A sample of 180 farm households is selected for interviews by using a multistage, random sampling technique. This study employed a probit regression model, frequency counts, and percentages to analyze the data. Access to formal agricultural credit is relatively low in Sindh province of Pakistan, the findings of the study show that the major constraints comprise distance to the formal credit sources, lending procedure, time lag, and interest rate whereas land ownership has a negative association and reduces the constraints to access formal credit. The findings of this study also show that for efficient allocation of resources, institutional sources of credit preferred to disburse agricultural credits toward educated and young age farmers as they are more inclined to adopt new farm technology for better farm production.