No abstract

Massive increase in crimes has coexisted with rising inflation and high unemployment for the last couple of decades especially during democratic governments in Pakistan. In this paper, we explore the relationship between crime rate, misery index and democracy in Pakistan from 1975 to 2013. Granger causality test proposed the unidirectional causality running from misery index to crime rate in Pakistan. Estimating the crime function via Pasaran's conditional error correction model, we found the significant long run equilibrium relationship between Okun's misery index and crime rate which implies that rising inflation and unemployment rate are the major driving forces towards increasing crime rates in Pakistan. Finally, empirical evidence from Okun's misery index suggested that people are three times more miserable in quasi democratic periods than that of dictatorship. The Barrow's misery index model verifies that people are twice worsening in quasi democratic periods. Likewise, reported crimes are nearly twice during quasi democracy than quasi dictatorship. The crime model provided the evidence that people during quasi democratic governments are more likely tending towards crime as compared to quasi dictatorship during the study period in Pakistan. This implicitly advocates the fact that half hearted efforts and ill structured apparatus of democracy can augment the tendency of crime and misery rather than solution of such concerns of the economy.

No abstract

Innovation adoptions in agriculture sustain high total factor productivity (TFP) growth and overcome a potential production gap, which is beneficial for food security. Research and development (R&D) innovation adoption in agriculture sector is dependent on producers’ willingness to adopt, knowledge capital spillovers, and financial capacity. This research aims to investigate the impact of R&D innovation adoption and climate factors on agriculture TFP growth in Pakistan. The annual time series data were collected from different sources for the period of 1972–2020. For measuring the agriculture TFP, this study adopted the Cobb Douglas and Translog production functions. To analyze the impact of R&D innovation adoption and climate change on agricultural productivity, the dynamic autoregressive distributive lag (ARDL) and two-stage least square (TSLS) approaches were applied for regression analysis. The study outcomes highlight that the agricultural innovation adoption has a significantly positive impact on agriculture TFP growth in Pakistan with weak farmers’ absorptive ability. According to the results, agriculture tractors, innovative seed distribution, and fertilizer consumptions make a significantly positive contribution to agriculture TFP growth. Further, rainfall shows a positive and significant impact on agricultural productivity, where a moderate climate is beneficial for agricultural productivity. The estimation results contain policy suggestions for sustainable R&D adoption and agrarians’ absorptive ability. Based on the obtained results, it has been suggested that producers should focus on R&D innovation adoption to attain higher productivity. The government needs to emphasize innovative technology adoption, specifically to implement the extension services to increase farmers’ education, skills based training, and networking among the farmers to enhance their knowledge capital and absorptive ability. The farmers should also focus on the adoption of climate smart agriculture that can be achieved through the proper utilization of rainwater. For this purpose, the government needs to develop small community dams and large-scale dams for better use of rainwater harvesting.

This research entails investigation of the impacts of Research and Development (R&D) spillover and irrigation water use efficiency on agricultural productivity in Pakistan. Influenced through the importance of R&D spillovers in innovation, water scarcity, irrigation technology, internal and external R&D shocks, human capital, agriculture employment and land were analyzed in the agricultural productivity. Considered the research objectives the annual timeseries data is collected for the period of 1973 to 2020 from different sources. The Autoregressive Distributed Lag (ARDL) model is applied to investigate the contribution of knowledge spillover and water resources efficiency for agricultural production in Pakistan. The results suggest the presence of positive and significant impact of foreign and domestic R&D spillovers on agriculture productivity of Pakistan. Further, the study found presence of larger positive externalities associated with external R&D spillovers in agriculture productivity. The estimates highlight that efficient utilization of water technology performs positive role in agriculture productivity in Pakistan. The results of both human capital and interactive term have negative sign and are significant which has clearly indicated that agriculture labor has less absorptive ability of foreign knowledge spillover. From the estimated results, it is recommended that government needs to focus on availability and accessibility of advance technology for farmers through increased outreach and extension services to educate the farmers and accelerate adoption of innovation in agriculture. Further, it is recommended that the Pakistani government must focus on the exploration of alternative irrigation technology in agriculture production for efficient use of water to increase agriculture productivity. Through the adoption of advanced irrigation techniques, the farmers can conserve the irrigated water, enhance water use efficiency in food production and overcome climatic challenges for agriculture production as well as food insecurity issues in Pakistan.