消费结构的收敛

消费结构的收敛内容摘要：

P shocks. 5. Data and Parameters Used for Simulation We set the length of one period to be one month. We work with 1000 employees – consumers,on the start of the program we distribute them equally among five ine groups. Based on the Statistics of Family Accounts we calculate the original distribution of outlays for each consumption type of each ine group. We add the highest ine group, where the original distribution is calculated from the data for Germany. The original distributions are in Figure 5. Consumption structure in the EU differs especially in food and beverages, where the share of outlays in the EU is lower, it is evident that this share decreases with growing ine in the Czech Republic as well. Considerable difference is in education, the outlays in the CR are just marginal. The average ine per person in the CR is CSK, starting employee’s ine is calculated from the starting distribution of outlays among branches and from the distribution into ine groups. Starting number of employees in each branch we calculate so as to get the same average wage in each branch. We assume that the distribution of employees into ine groups is the same for all branches. We assume that the structure of consumption in the EU is constant during the convergence period. 6. Discussion of Simulation Results We set the default parameters of the model to: w0 =。 w1 =。 w2 =。 w3 =。 w4 =。 w5 = . With these parameters, the most decisive motive for each consumer is his or her previous consumption (weight 50 %). Both the membership in an ine group and in an employees group have the same influence on the consumption decision (weight 20 %). The weight with that the consumers take the decisions of all consumers into account is 15%. The negative social correlation has twice as high weight as the aspiration towards higher social group (10 % and 5 %). With these default parameters, the development of total ines of sectors – industrial branches during the first 50 iterations is in Figure 6. We can see a clear tendency of decrease in expenditures on food and beverages and increase in expenditures on housing and education. In Figure 7 and Figure 8 we can see the development of expenditures for these consumption types for specific ine groups. It is evident that after a couple of periods, all ine groups will converge toward the EU. In Figure 9 we can see that after 50 iterations, the structure of consumption in the fourth and fifth ine groups is in principle identical to the structure in the EU and even the differences for the three lower ine groups are not big. So the model suggests, that the structure of consumption in the CR can approach the structure of consumption in the EU15 in 50 periods (about 4 years). The convergence of the model with chosen parameters is pleted approximately after 140 periods (about 12 years). To present this result in a similar way as in the empirical analysis of convergence, we use in Figure 10 the sum of variances as the measure of convergence. 7. The impact of changes of the tax rate on the speed of convergence With the growth of the tax rate the differences among ines diminish. Above the 60% tax rate, the redistributional effect is so high that we get strong fluctuations in both ines and expenditures. Bellow the 60% tax rate, we do not get any considerable impact of the tax rate changes on the speed of convergence. In Figure 11 and Figure 12 we can see the。