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Our estimation results show that a capacity coordination policy that forces firms to reduce their excess production capacity can effectively reduce excess capacity without distorting firms' scrapping decisions or increasing firms' market power. 2Preceded by this law, a similar law called "the Temporary Law for the Stabilization of the Special Recession. By the end of March 1986, the divestment plan related to the Temporary Law for the Structural Improvement of the Special Industries was completed.

However, at that time, the cement industry faced a new challenge, namely, a sharp assessment of the yen after the Plaza Agreement in September 1985. Due to rising imports and falling exports, excess capacity remained despite the end of the investment plan. Although the cement industry was not subject to this previous law, many other industries subject to the Temporary Law on the Structural Improvement of Special Industries were also subject to the previous law.

4This group remained after the removal of the Provisional Law for the Structural Improvement of Special Industries (Japan Cement Association, ed., 1998: p. 53).

Figure 1: Industry Evolution over Time
Figure 1: Industry Evolution over Time

3 Empirical Analysis

Why did not the Firms Divest?

Motivated by these theoretical explanations of why firms have an incentive to maintain their production capacity, we empirically investigate whether having (excess) capacity affects the production and investments of other firms. Moreover, there is another reason to check the production quantity of the other companies. Impact of overcapacity on investments We then empirically investigate the second channel: whether the (over)capacity of other companies influences investments.

If our hypothesis is true, no divestment by other firms in the previous periods leads to divestment in the current period. The differences between (iii), (iv) and (v) are the number of higher order terms that are included: (iii) includes up to a second order term from other firms' quantities, but (iv) and (v) respectively include to third and fourth order terms. However, after controlling for the quantity produced by other firms as in Specification 2, other firms' capacity no longer has any impact.

The absence of any effect of other firms' capacity suggests that it plays a strategic role through the production behavior of other firms. In Specification 3, our interest is in other firms' investment coefficients, which are negative and statistically significant for both models. This result suggests that firms take into account the investment (disinvestment) behavior of other firms in the previous year when making investment (disinvestment) decisions this year.

In particular, the results mean that companies dispose of their capacity less when they observe divestments by other companies. These results are consistent with the hypothesis that firms delay divestment and wait for other firms to divest. Instead, the cement companies may have played an attrition game by not divesting their production facilities while expecting other companies to divest.

Table 3: Impact of Excess Capacity on Production
Table 3: Impact of Excess Capacity on Production

Which plants were divested?

The estimation results are shown in Table 4, while the production function results are summarized in Table B1 in Appendix B. The first, second, and third columns include year, firm, and area fixed effects, while the fourth through six columns include year only - and area fixed effects. Regardless of the productivity measures, the estimates of basic productivity, β1, are always positive and statistically significant at all levels, implying that firms are investing in more productive plants and divesting unproductive ones.

However, the productivity coefficients interacted with the 1985/1986 or 1988/1990 dummies, β2 and β3, respectively, and are statistically insignificant for all specifications, indicating that firms did not change their investment/sales decisions during the implementation of policies. These results are very robust and we can conclude that this policy did not distort the firms' scrapping decision rule. The results described above imply that inefficient facilities in a company were divested; but not necessarily that inefficient plants from a social point of view were disposed of.

Therefore, to answer this additional question, we drop fixed effects from the regression and the results are presented in the fourth through sixth columns of Table 4. As is clear from the results, the previous results still hold, not only qualitatively but also quantitatively. , meaning that the divested factories were not only individually inefficient, but also socially inefficient. A simple production process, one of the hallmarks of this sector, allowed the regulator to easily measure the unnoticed productivity of the factories, and the system of side payments helped the companies agree on the allocation.

Table 4: Divestment Decisions with Three Productivity Measures
Table 4: Divestment Decisions with Three Productivity Measures

Impact on Prices and Markups

The first column, labeled (i) OLS, shows the regression results without using any instruments, while the rest of the specifications use an instrument, but the flexibility of year is different in each case. So, to mimic this pattern, we need to include at least the third order term of the year effects. Including the higher order terms of year effects does not change our quantitative results from those in models (iii) and (vi).

Regardless of the specifications, the coefficients for the 1985/1986 and 1988/1990 indicator variables are not statistically significant, implying that the policy had no effect on markups. The reason that the coefficient for the 1985/1986 dummy is insignificant is because most of the capacity eliminated during the first capacity coordination policy was non-operational capacity. So even though the companies closed these factories, the companies' market power remained unaffected.

Regardless of specification, the positive and statistically significant coefficients on the 1988/1990 dummy variable indicate that firms increased their remaining plant utilization rates to meet demand during the second policy intervention. The results are qualitatively similar to the case with TFP.8 The coefficient of capacity is positive but not statistically significant, which means that capacity has no effect on production cost. Based on our analysis, we conclude that policy interventions did not have any significant impact on the valuations charged by firms.

In conclusion, if the government were to reduce production capacity a little more, then there would be excess demand which would probably increase the market power of firms. Therefore, the amount of capacity reduction was key to the success of the policy, and we discuss this issue further in Section 4. At the same time, although we control for plant fixed effects and productivity measures, this may be for due to endogeneity: firms can increase output in those factories with the lowest marginal cost.

Figure 3: Transition of the Nominal Portland Cement Price in Japan
Figure 3: Transition of the Nominal Portland Cement Price in Japan

4 Policy Implications and Caveats

Moreover, even without perfect information on the productivity of each factory, regulators can induce private firms to design a mechanism that would efficiently allocate investment. Indeed, under policy private firms in the Japanese cement industry developed such a mechanism with side payments through negotiations. Determining how much capacity should be shed in the industry as a whole is another challenge.

This question again raises the information problem: the government may not be able to accurately predict future demand, while firms in the industry have better information about demand and supply. If regulators can predict future demand with high accuracy, they can correctly measure excess capacity. In fact, immediately after the policy intervention between December 1986 and February 1991, the Japanese economy experienced a boom called the "Heisei bubble," and cement demand recovered during this period, as shown in panel (a) of Figure 1.

Although net exports were consistently positive, the cement industry had to reduce exports and increase imports during this period to meet domestic demand. In this regard, we find no evidence of such anti-competitive behavior in the Japanese cement industry after the implementation of the policy, whereas the Aloha–Hawaii case encouraged cooperation for several years until new entrants entered the market. Another dynamic consequence that our analysis cannot capture is whether this policy extended the life of inefficient firms.

Thanks to this political intervention, some inefficient companies survived during periods of low demand. Without this policy intervention, some inefficient firms would have been forced out of the market. To predict such a dynamic consequence, we need to build a structural dynamic model, as done by Nishiwaki (2016).

5 Conclusion

While this may be an infrequent occurrence in declining industries, it is important that policymakers keep such possibilities in mind when developing policies. Dynamic Consequences As Kamita (2010) has noted, capacity coordination is essentially an anti-competitive policy and can lead to collusion over time. Using plant-level data on the Japanese cement industry, this paper empirically studies the effectiveness of a capacity coordination policy that forces firms to simultaneously reduce their production capacity.

Our estimation results show that a capacity coordination policy can effectively reduce excess capacity without distorting firms' scrapping decisions or increasing their market power. Although this series of policy interventions appears to be successful, some caveats apply in relation to capacity coordination policy in other industries/countries: (i) estimation of excess capacity and its allocation and (ii) dynamic effects and consequences of the policy intervention. Therefore, politicians interested in introducing capacity coordination policy must keep these caveats in mind.

Hampton, Kyle, and Katerina Sherstyuk, “Demand Shocks, Capacity Coordination, and Industry Performance: Lessons from the Economics Laboratory,” RAND Jouranl of Economics. Japan Cement Association, ed., 50-Year History of the Japan Cement Association (Cement Ky¯okai 50-nen no Ayumi), Tokyo: Japan Cement Association, 1998. An Empirical Analysis of Capacity Divestitures and Production Reallocations in the Japanese Cement Industry,” Journal of Industrial Economics.

R¨oller, Lars-Hendrik and Frode Steen, “On Cartel Performance: Evidence from the Norwegian Cement Industry,” American Economic Review.

Appendix A: Side-Payment Scheme for Divestment Al- lotment

Appendix B: Production Function Estimation

参照

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