Determinants of agricultural entrepreneurship: a GEM data based study

The aim of this study is to explain the determinants of entrepreneurship in agriculture industry. What are the drivers of early stage entrepreneurial activity of agri-business entrepreneur and how it is influenced by various cognitive and social capital factors? To answers these questions various driving factors of entrepreneurial activity have been explored from the literature. To achieve the objective, the study uses APS (Adult Population Survey) 2013 data of 69 countries provided by GEM (Global Entrepreneurship Monitor). Total number of respondents 1470, those who are alone or with others, currently trying to start a new business, including any self-employment or selling any goods or services to others in Agriculture Industry, were selected from the data set. To measure the influence of cognitive and social capital factors on early stage entrepreneurial activity logistic regression was employed. The findings show that those who see entrepreneurial opportunities, are confident in their own skills and ability, having personal relationship or social networks with existing entrepreneurs, and have invested in others business as business angels are more likely to become an entrepreneur. Additionally, fear of failure or risk perception does not prevent people to become entrepreneur. Policy implications have been discussed. This is one the first study of its kind and contributes to the existing literature by explaining agricultural entrepreneurship through an integrated approach of entrepreneurial cognition and social networking.

     

‘Retweet for a Chance to…’: an analysis of what triggers consumers to engage in seeded eWOM on Twitter

Twitter provides an important channel for brands to seed electronic word of mouth (eWOM) by followers retweeting brand messages, but prior research has not established a theoretical framework for how brands can maximise eWOM. This study presents and tests a theoretical model incorporating interactive, textual and visual tweet features to predict eWOM, using tweets by leading brands from three industries. Industry was found to be an important moderator of the effect of tweet features; after controlling for the reach and frequency of tweets, hashtags, retweet requests and photos were consistently associated with a higher retweet rate across industries, but the effect of URL links, non-initial mentions and video varied across industries, in some cases decreasing the retweet rate. Implications for research and practice are discussed.     

Market reactions to policy deliberations on fair value accounting and impairment rules during the financial crisis of 2008–2009

Fair value accounting (FVA) has been blamed for amplifying the financial crisis of 2008–2009. We investigate investor and creditor reactions to policymaker deliberations, recommendations and decisions about FVA and impairment rules in the banking industry. If FVA was a key contributor to the financial crisis as some industry pundits and academic research suggest, we first should observe positive stock market reactions to proposals that relax FVA rules and negative reactions when policymakers support FVA. Second, we investigate cross-sectional stock price reactions to bank-specific factors that potentially contributed to pro-cyclical contagion. Third, we examine whether banks that have fewer alternative sources of information about fair values experience relatively negative reactions to potential relaxation of FVA and impairment rules. Finally, we investigate credit market reactions to these policy deliberations, recommendations and decisions by examining changes in credit default swap spreads for a subset of banks in our sample.     

Average out-of-pocket healthcare and work-loss costs of traffic injuries in Karachi, Pakistan

The objective of this study was to assess the average out-of-pocket healthcare and work-loss costs of road traffic injuries (RTI) in Karachi. In this cross-sectional study, RTI patients presenting to the five trauma centres in Karachi were contacted using stratified sampling to report their inpatient and outpatient expenses, the time spent in hospital and their average monthly income. These costs were compared among different categories of patient-related variables using analysis of variance test. Out of 341 RTI victims, two wheelers accounted for the majority of injuries (77.2%, N?=?256) followed by pedestrians (14.2%, N?=?48). Almost half of the sample patients were breadwinners (N?=?135, 45.2%), with 87.4% (N?=?118) earning less than US$ 248. Average out-of-pocket healthcare costs were US$ 271 (SD?=?440.9), which were significantly higher (P ≤ 0.026) for pedestrians (US$ 442), moderate (US$ 341.7) or severe (US$ 553.8) injury, and treatment in private hospitals (US$ 451.7). Similarly, average work loss was US$ 67.1 (SD?=?132.1), which were significantly higher (P?=?0.001) for breadwinners (US$ 99.1), moderate (US$ 130.0) or severe (US$ 157.1) injury, and treatment in private hospitals (US$ 150.0). Study results clearly showed the need to advocate RTI prevention measures in Pakistan as any such event could lead to a difficult economic situation for those involved and their family.     

The evolving role of agricultural technology indicators and economic growth in rural poverty: has the ideas machine broken down?

The objective of the study is to examine the impact of technical progress in agriculture on changes in rural poverty in Pakistan by using annual data from 1975–2011. Data is analyzed by the set of sophisticated econometric techniques i.e., cointegration theory, Granger causality test and variance decomposition, etc. The results reveal that agricultural technology indicators act as an important driver to alleviate rural poverty in Pakistan. Granger causality test indicate that causality runs from technological indicators to rural poverty but not vice versa. However, agricultural irrigated land and industry value added, both does not Granger cause rural poverty, which holds neutrality hypothesis between the variables. Variance decomposition analysis shows that among all the technological indicators, agricultural machinery in form of tractors have exerts the largest contribution to changes in rural poverty in Pakistan. The study concludes that agricultural technology indicators are closely associated with economic growth and rural poverty in Pakistan. Technology in Pakistan has a low pace but still old technology continuously contributed towards poverty reduction. The question whether idea machine is broken down or not? Still need further exploration.     

Nonparametric estimates of productivity and efficiency change in Australian Broadacre Agriculture

This paper computes and decomposes Färe‐Primont indexes of total factor productivity of Australian broadacre agriculture by estimating distance functions. Using state‐level data from 1990 to 2011, the empirical results show that TFP grew at an average rate of 1.36 per cent per annum in the broadacre agriculture over the period 1990–2011. There are variations of total factor productivity (TFP) growth across states and fluctuations over time within each state and territory. However, overall, there is a clear movement towards slower TFP growth across the sample period. Further decomposition of TFP growth shows that it is declining growth in technical possibilities (technological progress) that is the main driver of the declining trend in productivity growth in broadacre agriculture in Australia.     

Governing the transition to low-carbon futures: A critical survey of energy scenarios for 2050

There is a growing scientific consensus that limiting the increase in global average temperature to around 2 °C above pre-industrial levels is necessary to avoid unacceptable impact on the climate system. This requires that the developed countries’ emissions are radically reduced during the next 40 years. Energy scenario studies provide insights on the societal transitions that might be implied by such low-carbon futures, and in this paper we discuss how a greater attention to different governance and institutional issues can complement future scenario exercises. The analysis is based on a critical review of 20 quantitative and qualitative scenario studies, all of relevance for meeting long-term climate policy objectives. The paper: (a) analyzes some key differences in energy technology mixes and primary energy use patterns across these studies; (b) briefly explores the extent and the nature of the societal challenges and policy responses implied; and (c) discusses a number of important implications for the design and scope of future scenario studies. Our review shows that in previous scenario studies the main attention is typically paid to analyzing the impact of well-defined and uniform policy instruments, while fewer studies factor in the role of institutional change in achieving different energy futures. We therefore point towards a number of strategies of integrating issues of transition governance into future scenario analyses, and argue for a closer synthesis of qualitative and quantitative scenario building.     

On the Mitra–Wan forestry model: A unified analysis

We present a substantive and far-reaching generalization of the principal results in the economics of forestry, as formalized by Mitra and Wan (1986). Rather than a polarized dichotomy of linear and strictly concave, differentiable benefit (felicity) functions, we develop the theory in the context of functions that are supported at the golden-rule consumption and are not necessarily concave. Through a non-interiority condition on the set of zeroes of a resulting “discrepancy function,” we show the equivalence of finitely-maximal, maximal, minimal value-loss and optimal programs, and thereby answer questions left open by Brock and Mitra. Our synthesizing criterion is new to the capital theory literature, and in the concave setting, proves to be necessary and sufficient for the asymptotic convergence of good programs.