Impact of Wheat Price Changes on Farmers’Willingness to Participate in Fallow

After operating for four years,the fallow project in the groundwater funnel area of the North China Plain has produced an initial water-saving effect.However,groundwater funnel remediation is a long-term process,and grain price changes over time may affect farmers’willingness to participate in fallow.Based on the estimation by the Cobb-Douglas production function,the relationship between farmers’satisfaction with fallow compensation and planting income is analyzed based on survey data collected from farming households in Hebei,a typical province located in the groundwater funnel area.Using this data,the impact of wheat price changes on farmers’willingness to participate in fallow is simulated.The results indicate wheat price changes affect farmers’expected planting income and consequently their willingness to fallow;88%of farmers would be unwilling to participate in fallow with a 0.1 yuan per 500 g increase in the wheat price,whereas 71.4%of farmers would be willing to participate in fallow with a 0.2 yuan per 500 g decrease in the price.Finally,some policy implications are proposed,such as the recommendation that the fallow compensation should be adjusted according to the wheat price multiplied by the average wheat yield of the three years before fallow in the North China Plain.

A QUANTITATIVE MODEL FOR INTRADAY STOCK PRICE CHANGES BASED ON ORDER FLOWS

This paper proposes a double Markov model of the double continuous auction for describing intra-day price changes. The model splits intra-day price changes as the repetition of one tick price moves and assumes order arrivals are independent Poisson random processes. The dynamic process of price formation is described by a birth-death process of the double M/M/1 server queue corresponding to the best bid/ask. The initial depths of the best bid and ask are defined as different constants depending on the last price change. Thus, the price changes in the model follow a first-order Markov process. As the initial depth of the best bid/ask is originally larger than that of the opposite side when the last price is down/up, the model may explain the negative autocorrelations of the price of the best bid/ask. The estimated parameters are based on the real tick-by-tick data of the Nikkei 225 futures listed in Osaka Stock Exchanges. The authors find the model accurately predicts the returns of Osaka Stock Exchange average.

Markov-Switching Time-Varying Copula Modeling of Dependence Structure between Oil and GCC Stock Markets

This paper proposes a Markov-switching copula model to examine the presence of regime change in the time-varying dependence structure between oil price changes and stock market returns in six GCC countries. The marginal distributions are assumed to follow a long-memory model while the copula parameters are supposed to evolve according to the Markov-switching process. Furthermore, we estimate the Value-at-Risk (VaR) based on the proposed approach. The empirical results provide evidence of three regime changes, representing precrisis, financial crisis and post-crisis, in the dependence structure between energy and GCC stock markets. In particular, in the pre- and post-crisis regimes, there is no dependence, while in the crisis regime, there is significant tail dependence. For OPEC countries, we find lower tail dependence whereas in non-OPEC countries, we see upper tail dependence. VaR experiments show that the Markov-switching time- varying copula model performs better than the time-varying copula model.

The Impacts of the Growth of the Three Industries and Industrial Price Structural Changes on China’s Economic Growth between 1952 and 2019

This paper focuses on the impacts and effects of China’s growth of the three industries and price structural change on the real GDP growth rate.First of all,it presents a new accounting method for decomposing growth rates on the basis of existing accounting method for decomposing growth rates.By using this method,we can identify the impacts and effects of structural changes on the growth rate.The paper uses a new decomposition method to recalculate China’s industry-based real GDP growth rates between 1952 and 2019,focuses on the driving effect of growth of the three industries on the real GDP growth,and the impacts of price structural change on GDP growth rate and the contributin of the growth of the three industries on GDP growth rate.By analysis,this paper shows that between 1952 and 2019 China’s economic growth was mainly driven by the secondary industry,which had contributed to the economic growth by over 50%,the role of the tertiary industry in driving economic growth rose,but that of the secondary industry declined over the time;in the short run,the overall effect of the price structural changes of the three industries has a little impact on the economic growth,but the price change of each industry has strong effects,and the price structural change has signifi cantly changed the effect of the growth of the three industries on the real economic growth;in the long term,the price structural change plays a relatively big hindering effect on economic growth due to the Baumol’s cost disease.

SIMULATION OF INVENTORY POLICY FOR PRODUCT WITH PRICE AND TIME-DEPENDENT DEMAND FOR DETERIORATING ITEM

In a declining market for goods,we optimize the net profit in business when inventory management allows change in the selling prices n times over time horizon.We are computing optimal number of changes in prices,respective optimal prices,and optimal profit in each of the cycle for a deteriorating product.This paper theoretically proves that for any business setup there exists an optimal number of price settings for obtaining maximum profit.Theoretical results are supported by numerical examples for different setups(data set)and it is found that for every setup the dynamic pricing policy out-performs the static pricing policy.In our model,the deterioration factor has been taken into consideration.The deteriorated units are determined by the recurrence method.Also we studied the effect of different parameters on optimal policy with simulation.For managerial purposes,we have provided some“suggested intervals”for choosing parameters depending upon initial demand,which help to predict the best prices and arrival of customers(demand).