An empirical analysis of the money demand function in India

This paper empirically analyzes India’s money demand function during the period of 1980 to 2007 using monthly data and the period of 1976 to 2007 using annual data. Cointegration test results indicated that when money supply is represented by M1 and M2, a cointegrating vector is detected among real money balances, interest rates, and output. In contrast, it was found that when money supply is represented by M3, there is no long-run equilibrium relationship in the　money demand function. Moreover, when the money demand function was estimated using　dynamic OLS, the sign onditions of the coefficients of output and interest rates were found to be　consistent with theoretical rationale, and statistical significance was confirmed when money supply was represented by either M1 or M2. Consequently, though India’s central bank presently uses M3 as an indicator of future price movements, it is thought appropriate to focus on M1 or M2, rather than M3, in managing monetary policy.

The contribution of supply and demand shifts to earnings inequality in urban China

This paper examines the degree to which supply and demand shift across skill groups contributed to the earnings inequality increase in urban China from 1988 to 2002. Product demand shift contributed to an equalizing of earnings distribution in urban China from 1988 to 1995 by increasing the relative product for the low educated. However, it contributed to enlarging inequality from 1995 to 2002 by increasing the relative demand for the highly educated. Relative demand was continuously higher for workers in the coastal region and contributed to a raising of interregional inequality. Supply shift contributed essentially nothing or contributed only slightly to a reduction in inequality. Remaining factors, the largest disequalizer, may contain skill-biased technological and institutional changes, and unobserved supply shift effects due to increasing numbers of migrant workers.

A model of economic growth with saturating demand

This study presents a model of economic growth based on saturating demand, where the demand for a good has a certain maximum amount. In this model, the economy grows not only by the improvement in production efficiency in each sector, but also by the migration of production factors (labor in this model) from demand-saturated sectors to the non-saturated sector. It is assumed that the production of a brand-new good will begin after all the existing goods are demand-saturated. Hence, there are cycles where the production of a new good emerges followed by the demand saturation of that good. The model then predicts that should the growth rate be stable and positive in the long run, the above-mentioned cycle must become shorter over time. If the length of cycles is constant over time, the growth rate eventually approaches zero because the number of goods produced grows.

Tariff reductions and labor demand elasticities : evidence from Chinese firm-level data

International production fragmentation has been a global trend for decades, becoming especially important in Asia where the manufacturing process is fragmented into stages and dispersed around the region. This paper examines the effects of input and output tariff reductions on labor demand elasticities at the firm level. For this purpose, we consider a simple heterogenous firm model in which firms are allowed to export their products and to use imported intermediate inputs. The model predicts that only productive firms can use imported intermediate inputs (outsourcing) and tend to have larger constant-output labor demand elasticities. Input tariff reductions would lower the factor shares of labor for these productive firms and raise conditional labor demand elasticities further. We test these empirical predictions, constructing Chinese firm-level panel data over the 2000--2006 period. Controlling for potential tariff endogeneity by instruments, our empirical studies generally support these predictions.

Quasi-experimental evidence on the drivers of index-based livestock insurance demand in Southern Ethiopia

Microinsurance is widely considered an important tool for sustainable poverty reduction, especially in the face of increasing climate risk. Although index-based microinsurance, which should be free from the classical incentive problems, has attracted considerable attention, uptake rates have generally been weak in low-income rural communities. We explore the purchase patterns of index-based livestock insurance in southern Ethiopia, focusing in particular on the role of accurate product comprehension and price, including the prospective impact of temporary discount coupons on subsequent period demand due to price anchoring effects. We find that randomly distributed learning kits contribute to improving subjects' knowledge of the products; however, we do not find strong evidence that the improved knowledge per se induces greater uptake. We also find that reduced price due to randomly distributed discount coupons has an immediate, positive impact on uptake, without dampening subsequent period demand due to reference-dependence associated with price anchoring effects.

Production sharing, demand spillovers and CO2 emissions : the case of Chinese regions in GVCs

This study adopts the perspective of demand spillovers to provide new insights regarding Chinese domestic-regions' production position in global value chains and their associated CO2 emissions. To this end, we constructed a new type of World Input-Output Database in which China's domestic interregional input-output table for 2007 is endogenously embedded. Then, the pattern of China's regional demand spillovers across both domestic regions and countries are revealed by employing this new database. These results were further connected to endowments theory, which help to make sense of the empirical results. It is found that China's regions locate relatively upstream in GVCs, and had CO2 emissions in net exports, which were entirely predicted by the environmental extended HOV model. Our study points to micro policy instruments to combat climate change, for example, the tax reform for energy inputs that helps to change the production pattern thus has impact on trade pattern and so forth.

Determinants of inbound tourists in Cambodia : a dynamic panel data approach

Understanding the determinants of tourism demand is crucial for the tourism sector. This paper develops a dynamic panel model to examine the determinants of inbound tourists to Siem Reap airport, Phnom Penh airport, and land and waterway borders in Cambodia. Consistent with the consumer theory of tourism consumption, a 10% increase in the origin country GDP per capita is predicted to increase the number of tourist visits to Siem Reap airport by 5.8%. A 10% increase in the real exchange rate between the origin country and Cambodia is predicted to decrease the number of tourist visits by 0.89%. In contrast, the number of foreign tourists in a previous period has little effect on the number of foreign tourists in the current period. Additionally, the determinants are different by the mode of entry to Cambodia.

Forecasting inbound tourists in Cambodia

Forecasting tourism demand is crucial for management decisions in the tourism sector. Estimating a vector autoregressive (VAR) model for monthly visitor arrivals disaggregated by three entry points in Cambodia for the years 2006–2015, I forecast the number of arrivals for years 2016 and 2017. The results show that the VAR model fits well with the data on visitor arrivals for each entry point. Ex post forecasting shows that the forecasts closely match the observed data for visitor arrivals, thereby supporting the forecasting accuracy of the VAR model. Visitor arrivals to Siem Reap and Phnom Penh airports are forecast to increase steadily in future periods, with varying fluctuations across months and origin countries of foreign tourists.

Cooperation in the knowledge transfer process: evidence from the demand side in Mexico

This paper presents the results of the analysis focused on scientific-technological KT in four Mexican firms and carried out by the case study approach. The analysis highlights the use of KT mechanisms as a means to obtain scientific-technological knowledge, learning, building S&T capabilities, and achieve the results of the R&D and innovation by firms.

Next Generation of Energy Residential Gateways for Demand Response and Dynamic Pricing

Predictions about electric energy needs, based on current electric energy models, forecast that the global energy consumption on Earth for 2050 will double present rates. Using distributed procedures for control and integration, the expected needs can be halved. Therefore implementation of Smart Grids is necessary. Interaction between final consumers and utilities is a key factor of future Smart Grids. This interaction is aimed to reach efficient and responsible energy consumption. Energy Residential Gateways (ERG) are new in-building devices that will govern the communication between user and utility and will control electric loads. Utilities will offer new services empowering residential customers to lower their electric bill. Some of these services are Smart Metering, Demand Response and Dynamic Pricing. This paper presents a practical development of an ERG for residential buildings.

Ubiquitous green computing techniques for high demand applications in smart environments

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

Neural network controller for active demand side management with PV energy in the residential sector

In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation.