A NOTE ON POPULATION AGING AND EFFECTIVENESS OF FISCAL POLICY

This paper examines how population aging affects the output effect of a government spending shock by using a panel data of OECD countries. The government spending shock is identified as a forecast error of government spending, and its output effect is estimated by using the local projection method. We find that population aging affects the output effect of the government spending shock. While in non-aging economies, government spending shock increases output significantly in both short- and medium-terms, in aging economies, output responses are not statistically significant.

An Estimation of Macroeconomic Energy Rebound, Intensity, and Output Effect: A Fresh Evidence from Pakistan

The authors have requested that this preprint be removed from Research Square.

A Study on the Health Output Effect of Chinese Medical Service Industry Agglomeration Based on Big Data Analysis

The agglomeration health output effect of the medical service industry in the era of big data is an important part of the agglomeration innovation of medical resources. This paper used the regression model of data mining to set up the fixed effect model and system GMM model to study the relationship between the agglomeration of medical service industry and resident’s health level, based on the panel data of 31 provinces of China from 2003 to 2017. The results show that the health outcome of the medical industrial agglomeration is positive and different in provinces. The influence of medical service cluster on residents’ health level in the eastern region fails the significance test, while the medical service cluster in the central and western regions can significantly improve residents’ health level. And, this effect is also related to the characteristics of medical resources, economic development, demographic characteristics, and other heterogeneous factors. On this basis, the paper puts forward policy suggestions to promote the market structure of the medical industry from the aspects of strengthening synergies and policy guidance.

Analysis of the Influencing Factors of Regional Carbon Emissions in the Chinese Transportation Industry

Global warming caused by excessive emissions of CO2 and other greenhouse gases is one of the greatest challenges for mankind in the 21st century. China is the world’s largest carbon emitter and its transportation industry is one of the fastest growing sectors for carbon emissions. However, China is a vast country with different levels of carbon emissions in the transportation industry. Therefore, it is helpful for the Chinese government to formulate a reasonable policy of regional carbon emissions control by studying the factors influencing the carbon emissions of the Chinese transportation industry at the regional level. Based on data from 1997 to 2017, this paper adopts the logarithmic mean divisia index (LMDI) decomposition method to analyze the influencing degree of several major factors on the carbon emissions of transportation industry in different regions, puts forward some suggestions according to local conditions, and provides references for the carbon reduction of Chinese transportation industry. The results show that (1) in 2017, the total carbon emissions of the Chinese transportation industry were 714.58 million tons, being 5.59 times of those in 1997, with an average annual growth rate of 9.89%. Among them, the carbon emissions on the Eastern Coast were rising linearly and higher than those in other regions. The carbon emissions in the Great Northwest were always lower than those in other regions, with only 38.75 million tons in 2017. (2) Economic output effect is the most important factor to promote the carbon emissions of transportation industry in various regions. Among them, the contribution values of economic output effect to carbon emissions on the Eastern Coast, the Southern Coast and the Great Northwest continued to rise, while the contribution values of economic output effect to carbon emissions in the other five regions decreased in the fourth stage. (3) The population size effect promoted the carbon emissions of the transportation industry in various regions, but the population size effect of the Northeast had a significant inhibitory influence on the carbon emissions in the fourth stage. (4) The regional energy intensity effect in most stages inhibited carbon emissions of the transportation industry. Among them, the energy intensity effects of the North Coast and the Southern Coast in the two stages had obvious inhibitory influences on carbon emissions of the transportation industry, but the contribution values of the energy intensity effect in the Great Northwest and the Northeast were positive in the fourth stage. (5) Except for the Great Southwest, the industry-scale effects of other regions had inhibited the carbon emissions of transportation industry in all regions. (6) The influences of the carbon emissions coefficient effect on carbon emissions in different regions were not significant and their inhibitory effects were relatively small.

Exploring the Output Effect of Fiscal Policy Shocks in Low Income Countries

What do we know about the output effects of fiscal policy in low income countries (LICs)? There are very few empirical studies on the subject. This paper fills this gap by estimating the output effects of government spending shocks in LICs. Our analysis—based on the local projection method—finds that the output effects in LICs are markedly lower than those in AEs and marginally smaller than those in EMs. We also find that in LICs, the output effects are larger (i) during recessions; (ii) under a fixed exchange rate regime; and/or (iii) with higher quality of institutions. Our analysis could not confirm any statistically significant output effect under floating exchange rate regimes. For the estimation of the output effects of fiscal spending shocks, it is thus important to consider the state of the economy and the country’s structural characteristics. Our results imply that the output costs of fiscal adjustment in LICs may not be as large as previously thought, especially if adopted outside of a recession, based on cutting public consumption, and accompanied by reform to enhance institutions.

Technological Advance, Economic Growth and Anti-trust of Intellectual Property

In market economy, there are four types of markets: perfect competition, monopolistic competition, oligopoly, monopoly. The main differences among them are the ability to set price, barrier to enter and exit the market, numbers of companies. To study innovation’s efficiency in these markets, it is necessary to understand their special characteristics. To simplify the problem, when patent is employed, only the innovation company has the access to this new technology. When it does not exist, every company in the market can use the new technology. In perfect competition market, there are no barrier to enter or exit and lots of companies producing identical products, so no company can set the price. Because there is no barrier, companies that can earn profit will enter the market, which decreases the price. Eventually, all companies’ marginal cost, average cost and marginal benefit is equal to the price, average benefit. In other words, companies in perfect competition market earn zero economic profit. Social welfare is always maximum in this type of markets. In this case, when one company discovers new production technology, other companies will follow immediately. Lower cost causes higher supply, which makes the price decrease and equal to the average cost eventually, leaving every company having zero economic profit, including the first company discovered the new technology, so there is no incentive for any company to spend resource on innovation. However, consumers’ welfare would increase because of lower price. When patent is employed, one company can produce products in a lower price and earn certain economic profit, but can hardly make an influence on the market because there are too many suppliers. Thus, in perfect competition market, patent is a good way to provide incentives for innovations. In monopolistic competition market, there are lots of companies selling slightly different products. The difference among products enables one company to increase the price over in a limited range, so monopolistic competition market is inefficient. In this type of markets, there are two types of innovations: technology and product. The former one reduces the cost and has the same consequence as that in perfect competition market. The latter one, product innovation, makes the product more special, giving the company more market power. However, without patent, product innovation will be copied easily, making the original product less special and canceling out the market power gained by the original company. Since there is no economic benefit, there is no incentive for any company in the market to innovate. When patent is employed, products’ difference is kept and gives the company more market power since there is consumer preference in monopolistic competition market. This increase of market power is not as negligible as that in perfect competition market, so the market becomes less efficient when the company with patent increases the price. In oligopoly market, there are only a few companies with great market power, so all of them can set the price. In this market, companies make decision based on both output and price effects. Output effect means when price is higher than marginal cost, companies can increase profit by increase its output. Price effect means when a company increases its output, the market price goes down, causing less profit for the company. When output effect is more impactful than price effect, companies will increase sales. When price effect is more impactful than output effect, companies will decrease sales. Oligopoly market can be inefficient without restrictions. Regarding innovations, there is still no incentives without the presence of patents. With patent, innovation company will gain market power that is huge enough to cause inefficiency and even to force other companies to exit the market. Thus, patent in oligopoly market will cause negative impact on society, which should be limited. The last type of markets if monopoly. In monopoly market, there is only one company, so patent is necessary. When this company innovates and decreases its production cost, it will tend to increase its output to maximize profit, which enlarges consumers’ welfare. However, this increase is not as much as that in perfect competition market, so innovation in monopoly market is still inefficient.

STATISTICAL CHARACTERISTICS OF THE ENERGY-CONCEALED PHASE-MANIPULATED SIGNAL

The law of distribution of the output effect differs from the normal one at the output of the receiving path realized on the basis of autocorrelation algorithm with quadrature processing. When there is no signal at the input of the receiver, the distribution of the output effect corresponds to Rayleigh’s or Rayleigh – Rice’s law in condition of its presence. The probability density distribution at the output of an incoherent auto correlation receiver with quadrature processing is considered in relation to the input level of the energy-concealed phase-manipulated signal. In order to detect a useful signal it is necessary that, at the output of the receiver, the signal / noise ratio exceeds the detection threshold determined by the Neumann – Pearson criterion according to the given probability of false alarm. The level of the signal-to-noise ratio at the output of an incoherent autocorrelation receiver with quadrature processing has been calculated. A characteristic feature of the presented graphs is the linear dependence of the output signal / noise ratio relative to the input signal. This feature is observed in the input signal / noise ratio which is less than one. The curves for the distribution of the probability density of the input signal mix and noise corresponding to the generalized Rayleigh’s law (Rayleigh-Rice) are constructed in the book. There is a shift of curves for the abscissa axis according to the given probabilities of false alarms and accumulation time (observation). It is evident from the given graphs that the offset of the abscissa of the input signal value / noise ratio significantly depends on the accumulation of the input mixture time. The curves for detecting an energy-concealed phase-manipulated signal by a non-coherent autocorrelation receiver with quadrature processing on the basis of the probability density distribution are obtained. The results of the calculations indicate that detection of a phase-manipulated signal on the background of "white" noise is possible in case of an input-to-noise ratio of less than one, that is, up to -32 dB in real time (up to 0.1 s).

Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities

With continuous industrialization and urbanization, cities have become the dominator of energy consumption, to which industry is making leading contribution among all sectors. Given the insufficiency in comparative study on the drivers of energy use across cities at multisector level, this study selected seven representative cities in China to quantify and analyze the contributions of factors to changes in final energy use (FEU) in industrial aggregate and sectoral levels by using Logarithmic Mean Divisia Index method. Disparities in the drivers of industrial FEU across cities were explicitly revealed within two stages (2005–2010 and 2010–2015). Some key findings are presented as follows. Alongside the increase in industrial output of seven cities within two stages, the variation trends in industrial FEU are different. Industrial output effect (contribution rate 16.7% ~ 184.0%) and energy intensity effect (contribution rate −8.6% ~ −76.5%) contributed to the increase in aggregate FEU positively and negatively, respectively. Beijing had the largest contribution share of industrial structure effect (−24.4% and −12.8%), followed by Shenyang and Xi’an. Contributions of energy intensity effect and industrial output effect for Chemicals, Nonmetals, Metals, and Manufacture of equipment were much larger than those of other sectors. The results revealed that production technological innovations, phase-out of outdated capacities of energy intensive industries, and industrial restructuring are crucial for reduction in industrial FEU of cities. This study also provided reference to reasonable industrial layout among cities and exertion of technological advantages from a national perspective.