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Effects of restoration measures from the east Japan earthquake in the Iwate coastal area: application of a DSGE model

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Abstract

Restoration investment after an earthquake and tsunami can improve regional production, but effects of investment emerge differently in production, investment and consumption. Conventional economic models cannot reproduce such chronological nonconformity among economic indices. This study aims to analyze whether the dynamic stochastic general equilibrium (DSGE) model can duplicate the chronological restoration path and nonconformity, and quantifies the efficiency of the restoration measures, such as restoration investment with fund transfer and rebuilding subsidy, in the Iwate coastal region, where the east Japan earthquake hit. The analytical results are as follows: (1) consumption after the earthquake follows a hump-shaped path, where peak point of consumption was delayed from production peak, but then recovered; (2) private investment and labor demand decrease by more than self-restoration does when the restoration measures end; and (3) restoration investment with fund transfer and rebuilding subsidy improves the economy by accelerating the reconstruction of damaged capital stocks, and the benefits of these two measures outweigh their respective costs. These findings show that the influence of an unforeseen and disastrous earthquake can be explained well by the forward-looking decisions on consumption and savings (equal to investment) endogenizing in the DSGE model.

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Fig. 1

Source: Regional accounts on residents by city (Iwate Prefectural Government)

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Notes

  1. Earthquake disasters occur with very low probability. Thus, it may be suitable to assume the occurrence probability of an earthquake disaster follows a Poisson distribution or a Power distribution. Numerical algorithm to treat Poisson uncertainty in DSGE model was proposed (Posch and Trimborn 2013), but transition process of the rare event itself is nothing to do with occurrence probability of the events. In our model, the post-simulation is conducted using the impulse response method, which inputs a one-time shock at the first period. Hence, the frequency of earthquake occurrence is not thought to be a matter in this simulation, even though this model assumes normal distribution for the earthquake.

  2. To solve the model, Dynare ver. 4.4.3 (Juillard 1996) was used. Initial values are set as actual values to tell the effective starting points of iteration to this software, though the steady-state values of endogenous variables were calculated as letting the total factor productivity equal one.

  3. When total damage of private capital stocks was supposed to be 1/3 of the total assets (lest of them was the private houses and public capital stocks) and was 5.6 trillion yen (= 16.9 trillion yen/3), such damage value accounts for about 5% of total private capital stocks in disaster prefectures (Aomori, Iwate, Miyagi, Fukushima and Ibaraki) (JIP database), which was 1.65 (= 0.05/0.03) times higher than the normal rate.

  4. Based on JIP database, total factor productivity (TFP) decreased in whole country by about 2.5% (average of all industries). Since gross regional production (GRP) of disaster areas was about 7% of total Japanese GDP and half of such decrease might be caused by the damage of nuclear power plant, a decrease in TFP by the earthquake and tsunami of these disaster areas is supposed to be 20% (≒ 2.5/2/0.07).

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Acknowledgements

This study was supported by the Grant-in-Aid for Scientific Research 16H04991 and 16KT0036 (Ministry of Education, Science, Sports and Culture) and Council for Science, Technology and Innovation, Cross-ministerial Strategic Innovation Promotion Program (SIP), Infrastructure Maintenance, Renovation, and Management. The authors greatly appreciate their support.

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Correspondence to Yoji Kunimitsu.

Appendix

Appendix

This section explains how to derive the equations relating to the production sector under monopolistic competition. These explanations are based on Torres (2013). Similar documents can be found in Eguchi (2011).

The final good is produced by a representative firm by aggregating the continuing of intermediate goods. This firm maximizes profits, Π, subject to the production function:

$$ \begin{aligned} \mathop {\hbox{max} }\limits_{{Y_{j,t} }} \;\varPi_{t} = P_{t} Y_{t} - \int_{0}^{1} {P_{j,t} Y_{j,t} {\text{d}}j} \hfill \\ {\text{s}} . {\text{t}} .\quad Y_{t} = \left[ {\int_{0}^{1} {Y_{j,t}^{{^{{\frac{\xi - 1}{\xi }}} }} {\text{d}}j} } \right]^{{\frac{\xi }{\xi - 1}}} , \hfill \\ \end{aligned} $$
(7)

where Y t and Y j,t are the final good production and intermediate goods production, respectively, differentiated by j at time t; P t and P j,t are the price of the composite final good and the prices of intermediate goods, respectively; and ξ(> 1) is the elasticity of substitution across intermediate goods. This method used to aggregate the intermediate goods is the Dixit–Stiglitz aggregator.

The first-order condition derives the following equation:

$$ Y_{t} = \left( {\frac{{P_{t} }}{{P_{j,t} }}} \right)^{ - \xi } Y_{j,t} \quad \forall \;j. $$
(8)

Each intermediate good j is assumed to be produced by only one firm, and optimizes production costs, as:

$$ \begin{aligned} \mathop {\hbox{min} }\limits_{{L_{j,t} ,K_{j,t} }} \;{\text{Cost}} = W_{t} L_{j,t} + R_{r} K_{j,t} + \varPhi_{j} \hfill \\ {\text{s}} . {\text{t}} .\quad Y_{j,t} = A_{t} K_{j,t}^{{\alpha_{1} }} Z_{j,t}^{{\alpha_{2} }} L_{j,t}^{{\alpha_{3} }} , \hfill \\ \end{aligned} $$
(9)

where Φ are fixed costs and assumed to be constant. The first-order conditions of the above problems derive the following equations:

$$ W_{t} = \lambda_{t} (1 - \alpha )Y_{j,t} /L_{j,t} , $$
(10)
$$ R_{t} = \lambda_{t} \alpha Y_{j,t} /K_{j,t} , $$
(11)

where λ t shows the Lagrange parameter and represents the shadow price of a change in the ratio of the use of capital and labor services.

The monopolistic firm determines the optimal price for the intermediate good they produce. The profit maximization problem to be solved is:

$$ \mathop {\hbox{max} }\limits_{{P_{j,t} }} \quad \pi_{j,t} = P_{j,t} Y_{j,t} - W_{t} L_{j,t} - R_{t} K_{j,t} . $$
(12)

Using Eqs. (8), (10), and (11), the above maximization problem can be defined as

$$ \mathop {\hbox{max} }\limits_{{P_{j,t} }} \quad \pi_{j,t} = P_{j,t} \left( {\frac{{P_{j,t} }}{{P_{t} }}} \right)^{ - \xi } Y_{t} - \lambda_{t} \left( {\frac{{P_{j,t} }}{{P_{t} }}} \right)^{ - \xi } Y_{t} . $$
(13)

The conditions \( \frac{{\partial \pi_{j,t} }}{{\partial P_{j,t} }} = 0 \) derive the following relation as:

$$ P_{j,t} = \frac{\xi }{\xi - 1}\lambda_{t} P_{t} . $$
(14)

In the steady state, the price of final good, P t , corresponds to the prices of the intermediate goods, P j,t . If all intermediate firms are assumed identical, the following equation is obtained:

$$ \lambda_{t} = \frac{\xi - 1}{\xi }. $$
(15)

Hence, the wage rate and rental rate under the monopolistic situation in intermediate production is given as:

$$ W_{t} = \frac{\xi - 1}{\xi }(1 - \alpha )A_{t} K_{j,t}^{{\alpha_{1} }} Z_{j,t}^{{\alpha_{2} }} L_{j,t}^{{\alpha_{3} - 1}} $$
(16)
$$ R_{t} = \frac{\xi - 1}{\xi }\alpha A_{t} K_{j,t}^{{\alpha_{1} - 1}} Z_{j,t}^{{\alpha_{2} }} L_{j,t}^{{\alpha_{3} }} . $$
(17)

These equations are used for the model as Eqs. (M1) and (M2).

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Kunimitsu, Y. Effects of restoration measures from the east Japan earthquake in the Iwate coastal area: application of a DSGE model. Asia-Pac J Reg Sci 2, 317–335 (2018). https://doi.org/10.1007/s41685-017-0055-z

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