Abstract. The goal of this paper is to carry out the comparative dynamic analysis of value added as part of total output created by the industry A02 (Forestry and logging) in the Baltic States (LTA, LTU, EST) and Finland (FIN) for the period of 2000-2014. The empirical material of the research is the "National Input-Output tables for the period 2000-2014" available on the World Input-Output Database (WIOD) with its unified structured statistical information in monetary terms. The discussion part of the paper is devoted to identification of the most important reasons, which cause significant differences in the economic efficiency of industry A02 in LTA, LTU, EST, FIN. The time series of value added as part of total output in the industry A02 are investigated. The comparative approach allows us to recognize sufficient differences in the shape of value added trends in the industry A02 in different countries. Coefficient of variation for value added calculated using trend corrected data is offered as original industry dynamics attribute. The version of input-output model is the theoretical tool to establish the most important reasons, which cause significant differences in the productivity of the industry A02 in LTA, LTU, EST, FIN (in the sense of value added creation).

The goal of this paper is to carry out a comparative analysis of value added as part of total output created by the industry P85 (Education) in the Baltic States and Finland in order to find an answer to the following question: "How realistic is a significant value added increase by the industry P85 in Latvia in the nearest years?" The empirical material of the research is the National Input-Output Tables for the Period 2000-2014 available on the World Input-Output Database with its unified structured statistical information in monetary terms. The theoretical background of the current research is the Input-Output analysis, which is further explored, for example, in the book Input-Output Analysis. Foundations and Extensions by Ronald E. Miller and Peter D. Blair and in some other scientific publications as well. The original version of the Input-Output model created by the author allows to calculate and to interpret the interindustry coefficients, Leontief inverse, allocation coefficients and Ghosh inverse. The author conducts a comparative analysis of direct and total linkages, backward and forward linkages of the industry P85 in the Baltic States and Finland in 2014 to estimate the impact of the increasing gross output in P85 on the national economy. The discussion part and conclusions of the paper are devoted to indetifying the most important factors, which cause significant growth of value added of the industry P85 in Latvia. The main conclusion: the most realistic way to attain an increase in value added of the industry P85 in Latvia is to encourage the export component of final demand with the help of well-organized higher education marketing.

Abstract. The goal of this paper is to conduct the comparative analysis of direct and total linkages, backward and forward linkages in the economies of the Baltic States and Finland in 2014. Measurement and comparison of the strengths of backward and forward linkages for the industries allow us to identify the "key" or "leading" industries of the national economy in the respective year, and to design certain clusters in order to classify the industries. We investigate the clusters of similar, in some sense, industries in the Baltic States and Finland, and offer an interpretation of the observed differences between these lists. The cluster analysis of the industry four linkages and share of industry output in the total output in five-dimensional space for Latvia, Lithuania, Estonia and Finland will be continued.

Abstract. This paper reconsiders the methods of measuring industry total factor productivity. The method offered by the honourable authors Ronald E. Miller and Peter D. Blair in their relevant book "Input-output analysis. Foundations and extensions. Second Edition. − Cambridge University Press, 2013" (14.2.1 Total Factor Productivity, pages 670-673) will be carefully tested. And it will be proved that the concept of the rate of total factor productivity growth offered in this book is inconsistent. With this, also decomposition of the change in total output of industry as "portion of change accounted for by using old technology to meet new input needs" plus "portion of change accounted for by using new technology to meet old input needs" is unsubstantial. The author realizes his serious liability for such categorical assertion about failure in the book presented under the famous "Cambridge University" brand and that is the reason why he bestows the authority upon the scientific conference to pass the sentence about correctness of his conclusions. In the second part of the present paper the original method of industry total factor productivity benchmarking within an input-output framework is offered. This method is grounded on the well-known Data Envelopment Analysis (DAE) using DAE modification by Jaunzems (2007). The main idea of this method is to compare the input-output capability of one and the same industry during one and the same time period in different countries. Thanks to the World Input-Output Database (WIOD) with its unified structured statistical information it is easy to carry out this method practically.Comparison of Latvia's agriculture industries A01, A02, A03 Input-Output converting relative efficiency with proper industries in the Baltic States and Finland (2000, 2014) gives original economic results never met before.Key words: input-output model, total factor productivity, modified data envelope analysis, industries benchmarking. IntroductionThe object of productivity measurement is the unit of production, which produces multiple outputs using multiple inputs. The developments in economic productivity measuring within an inputoutput framework have been summarized in the Journal of the International Input-Output Association , the authors explore the concept of total factor productivity (TFP), which is defined generally as the growth in total output that is not attributable to growth in inputs (14.2.1 Total Factor Productivity, pages 670-673).The current paper is devoted to two questions. Firstly, the method offered by the honourable authors Ronald E. Miller and Peter D. Blair in their relevant book will be carefully tested. It will be proved that the concept of the rate of total factor productivity growth offered in this book is inconsistent. With this, also decomposition of the change in total output of industry as "portion of change accounted for by using old technology to meet new input needs" plus "portion of change accounted for by using new technology to meet old input needs" is unsubstan...

The goal of this paper is to carry out the comparative dynamic analysis of value added as part of gross output created by the industry A01 (Crop and animal production, hunting and related service activities) in the Baltic States and Finland in the period of 2000-2014. The empirical material of the study is the National Input-Output Tables for the Period 2000-2014 available on the World Input-Output Database with its unified structured statistical information in monetary terms. The main theoretical tool is the original version of the Input-Output model created by the authors that allows to calculate and interpret the interindustry coefficients, Leontief inverse, allocation coefficients, Ghosh inverse. The time series of value added as part of gross output in the industry A01 are investigated. Although this indicator decreases in all examined countries, the comparative approach allows us to identify sufficient differences in the industry's A01 value added formation in the respective countries. The Input-Output model allows us to provide holistic investigation of the industry's A01 one monetary unit gross output production costs dynamics. The discussion part of the paper is devoted to identifying the most important reasons for differences in economic efficiency (in the sense of value added creation) of the industry A01 in the Baltic States and Finland. We define the objective and other reasons, which cause average cost increase in all examined countries. We also identify the differences in the structure of average cost vectors, which indicate historically formed and existing technological differences in A01 economy.