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By Sebastian Rausch

This publication provides a brand new computational method of fixing large-scale Auerbach-Kotlikoff Overlapping Generations (OLG) versions in a complementarity structure. in contrast to with built-in resolution tools, the proposed decomposition set of rules permits the answer of multi-regional and multi-sectoral OLG versions that convey a number of heterogeneous shoppers and various household-specific results. by way of broadening the scope of monetary research, this new method offers a strong software for utilized common equilibrium modelers. during this ebook, the set of rules is utilized to the macroeconomics of demographic switch, demonstrating its flexibility and scope as an answer notion. With a selected research at the implications of worldwide unsynchronized demographic styles for foreign alternate, the publication additionally explores the sectoral and distributional effects of an getting older inhabitants in Germany.

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003 0 1 5 10 15 20 25 30 Iteration Fig. 11 Solving OLG by Ramsey: approximation error ek tions of Γ . We set H = 50 so that the benchmark solution method is feasible and the calculation of approximation errors is available. Not surprisingly, the approximation quality of the method is decreasing with the degree of heterogeneity. Overall, the quality of approximation is still very good: computed prices fall within a reasonably small interval around the true equilibrium price path (τ k is around 10−5 − 10−3 ).

Lastly, households are not only heterogeneous with respect to their age but also exhibit fundamental differences in preferences and ability. This point is taken into account by allowing for 10 different household types within each generation. e. openess may be immiserizing. This is a result of the evolution of autarky-trade factor price differentials during the demographic transition. We find that, for the fast aging region, trade liberalization is only beneficial for current old generations that are born before and in the beginning of the demographic transition.

18) 2 min 06 s ( × ) 6 min 14 s ( × ) 10 min 48 s ( × ) 30 min 31 s ( × ) Note: Figures in parentheses denote running time of the decomposition algorithm expressed as a fraction of the running time as required by the benchmark simultaneous solution method. A “×” indicates infeasibility of the simultaneous solution method. 2 Approximation errors for different Γ Γ (H = 50) Number of iterations Approx. error ek (last iteration) Max. 22) Note: Figures in parentheses denote running time of the decomposition algorithm expressed as a fraction of the running time as required by the benchmark simultaneous solution method.

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