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We employ a non-parametric approach to examine the real exchange rate and the entire age distribution in South Korea. We find that movements of the real exchange rate are tightly related to the evolution of the demographic structure and that the estimated age response function is consistent with a life-cycle model in which older generation and younger generation have a positive effect on the real exchange rate. Finally, the real exchange rate is forecasted to appreciate gradually, which suggests that the growing proportion of the older population has a stronger impact than the falling proportion of the younger generation on the real exchange rate.

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This paper brings together analyses of two-way flow Strict Nash networks under exclusive player heterogeneity assumption and exclusive partner heterogeneity assumption studied by Galeotti et al. (2006) and Billand et al. (2011) respectively. We provide a proposition that generalizes the results of thesemodels by stating that: (i) StrictNash network consists of multiple non-empty components as in Galeotti et al. (2006), and (ii) each non-empty component is a branching or $B_i$ network as in Billand et al. (2011). This proposition requires that a restriction on link formation cost, which is called Uniform Partner Ranking, is satisfied.

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We utilize the copula function methodology to separate out the components which describe the marginal behavior of the return processes and the dependence structure between the random variables from the joint density. In order to reflect the non-ellipticity of the joint distribution and heavy tails in the extreme quantile of the marginal distributions of asset returns, we use the generalized Pareto distribution (GPD) as the margins and a variety of parametric copula functions along with a nonparametric copula function in the analysis. We select the optimal copulas from a variety of non-nested copulas based on the model selection criteria. In calculating the risk measures, we assume that the returns are jointly distributed to the parametric copulas as well as to the empirical copula. We then compare the result with that from the bivariate normal distribution. The results show that the VaR and ES computed from the copula function which takes the complicated and possibly nonlinear dependence structure into account performs better than the one based on the linear correlation-based normality assumption.

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This paper examines whether idiosyncratic firm-level shocks can explain an important part of aggregate movements as in Gabaix (2011). Its findings show that, different from the case in the United States, the idiosyncratic movements of the largest 20 firms in Korea appear to explain up to 18% of the variations in output growth between 1981 and 2011. In addition, they are also useful in explaining the cyclical component of GDP. It is found that the top three firms’ movements account for 58% of the cyclical component of GDP during the period from 2001q1 to 2012q3. This empirical evidence suggests that the granular hypothesis also holds in Korea.