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This paper aims to analyse the Portuguese companies’ determinants of capital structure. To reach this objective, the authors used data from 37 non-financial Portuguese large enterprises and from 4,233 non-financial small and medium enterprises for the period 2010-2016. Additionally, the authors selected a sub-period from 2010 to 2014 for a deeper understanding of the impact of the sovereign debt crisis and the Economic Adjustment Programme of Troika on the capital structure of those companies.

Three dependent variables were tested according to debt maturity, and a dynamic panel data model, namely, the generalised method of moments system estimator, was used to test the formulated research hypotheses following Arellano and Bover (1995) and Blundell and Bond (1998) to capture the dynamic nature of the firm’s capital structure decisions.

In general, the results point out that the capital structure decisions depend on a set of firm-specific factors, and that the effects of the determinants of the debt maturity ratios differ according to the type of firm, i.e. large/small firms, and the economic cycle.

To the best of the authors’ knowledge, this is the first study that has been carried out in Portugal by using two samples of large and small companies for analysing the effects of the Economic Adjustment Programme of Troika on the capital structure of companies. The authors seek to understand which type of companies suffered more because of the effects of the Economic Adjustment Programme of Troika during this period, and which are the capital structure determinants that present greater change. Contrary to what might be expected, large companies are the firms that suffer most from the Economic Adjustment Programme. Probably, because these companies are the most immediate, most scrutinised and those that must show abroad that the bank did not fund them in the long term, because of the imposition and limits to grant credit faced by the banks themselves.

The purpose of this paper is to propose and analyze a model to obtain a total factor productivity of an industry through quantitative empirical analysis in order to determine the joint contribution of the production and technology function, and the change and technical progress. The case of the Peruvian large shipbuilding industry between the years 1969 and 1990 was considered for the analysis of the proposed model. The large shipbuilding in Peru finished in 1992 and has restarted in 2014. The importance of the study lies in the fact that the analysis is focused on an industry which is resurfacing, and in this regards, the study of the first production period will yield more and accurate information to make decisions regarding its future development.

One way of considering the several effects of technical progress, in line with Sato (1970) such as growth and bias, is to specify a production function maintaining the linear homogeneity property, such as: Y(t)=F [A(t)K(t), B(t)L(t)], where Y(t) is the aggregate product over a period of time (t); K(t) is the capital; L(t) is the labor; and A(t) and B(t) are the efficiencies or augmentations of K(t) and L(t), respectively. Based on the regression analysis data, the value of σ can be estimated to a residual growth rate (Kennedy and Thirlwall, 1972) that allows assessing the technical knowledge that is not attributable to the factors’ efficiency grains: TCTR = T ˙ / T − ( α ( A ˙ / A ) + β ( B ˙ / B ) ) . This last expression measures the residual technological growth rate (TCTR, by its Spanish acronym).

The results of the analysis of the large shipbuilding at SIMA-Callao during the given period (22 years of operation, between 1969 and 1990) show that the necessary installed capacity and the technological knowledge was available in order to develop a complex industrial process in the South Pacific region, thus, contributing to the sector’s growth in the country. The evolution of the shipbuilding activities coincides with the GDP expansion and decline periods in Peru. According to the results, the total factor productivity increased during 1969-1976, 1979-1982, and 1986-1987 periods and it has been confirmed that the contribution of the efficiencies of the production factors were inversely related to the economies of scale and output growth.

The analysis is based on the activities carried out throughout 22 years of operations in SIMA-Callao shipyards (1969-1990). The data regarding the product, labor, imported materials costs, local material costs, direct expenses, wages, and man-day costs was obtained from several sources within the shipyard. Direct expenses correspond to classification, inspections, administrative expenses (dock, quality control, equipment rental, etc.), drawings, technical data, insurance, and materials freight. Additionally, the sources of information are project construction contracts, annual expenses reports, and man-day cost quarterly reports of the shipbuilding area. The man-day cost includes salary, social benefits, and the company’s functional cost.

There are different ways to obtain productivity index. In this case, the authors used the stated model. In addition, based on this experience, this can be applied to other industries.