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This study investigates the dynamic production structure of the Japanese manufacturing industry by using the adjustment cost approach. The study is to shed some light on the unique dynamic structure of the Japanese manufacturing industry. The study attempts to help design and predict industrial policies that are implemented to enhance domestic investments by the Japanese government.

This study obtains a system of dynamic factor demand and output supply equations by applying the dual approach to the intertemporal value function as represented by the Hamilton–Jacobi equation. By using industrial panel data for 1973–2012 of the Japanese manufacturing industry, the study estimates the system of the behavioral equations and corresponding elasticities. The study uses hypothesis tests and dynamic elasticities to investigate the dynamic structure of the Japanese manufacturing industry.

Estimation results show that labor and capital are quasi-fixed variables that adjust about 0.2 percent annually to the long-run optimum levels. Estimated adjustment rates are very slow as often presumed about the Japanese manufacturing industry, which uses lifetime employment practice and slow decision-making process in investment decisions. The results also show that output supply and factor demand elasticities vary greatly depending on time horizon. Factor demand increases when its own price increases in the short run, suggesting that factor adjustment is mostly determined factor prices in the past due to sluggish factor adjustment. However, factor demand becomes a normal downward-sloping curve in the long run as factor adjustment gets completed.

Japanese manufacturing firms hire employees through lifetime contract to exploit the benefits of dynamic learning-by-doing and execute investments carefully considering all the possible impacts. Under the strategy, adjustment costs for changing workers and capital stock are minimized. Dynamic adjustment model is expected to shed some light on the unique dynamic structure of the Japanese manufacturing industry. However, researches regarding the dynamic factor adjustment of the Japanese manufacturing industry are hard to find. This study is expected to fill the research vacuum.

The development of green manufacturing has become essential to achieve sustainable development and modernize the nation’s manufacturing and production capacity without increasing nonrenewable resource consumption and pollution. This study investigates the effect of green industrial practices on technical efficiency for Thai manufacturers.

The study uses stochastic frontier analysis (SFA) to estimate the stochastic frontier production function (SFPF) and inefficiency effects model, as pioneered by Battese and Coelli (1995).

This study shows that, on average, Thai manufacturing firms have experienced declining returns-to-scale production and relatively low technical efficiency. However, it is estimated that Thai manufacturing firms with a green commitment obtained the highest technical efficiency, followed by those with green activity, green systems and green culture levels, compared to those without any commitment to green manufacturing practices. Finally, internationalization and skill development can significantly improve technical efficiency.

Green industry policy mixes will be vital for driving structural reforms toward a more environmentally friendly and sustainable economic system. Furthermore, circular economy processes can promote firms' production efficiency and resource use.

To the best of the authors' knowledge, this study is the first to investigate the effect of green industry practices on the technical efficiency of Thai manufacturing enterprises. This study also encompasses analyses of the roles of internationalization, innovation and skill development.

Using a large firm-level data set, this paper examines total factor productivity (TFP) and its determinants in the Ecuadorian manufacturing sector in the period 2007–2018.

I analyze the role played by traditional TPF determinants, including internal firm characteristics, international trade activities, financial constraints and competition intensity. I contribute to the literature by presenting quantile regression results. Moreover, I analyze industry patterns, distinguishing between industries according to their technological intensity (following the organisation for economic co-operation and development classification).

My results confirm that firm age is positively related to TFP level but negatively related to TFP growth. I also find that being an exporter and an importer at the same time is associated with higher TFP levels and that this effect is higher than when being only an exporter or an importer. Additionally, l find that credit is positively related to TFP levels. Finally, I find that more competition is positively related to productivity in lower quantiles of output.

The results are the source of tools to propose policy recommendations, which are stated in the present document.

This paper aims to reopen the debate of firm productivity determinants in a developing country such as Ecuador. The authors use a set of covariates less analyzed in this issue.