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ABSTRACT: This article seeks to derive the determinants of labour productivity growth in the Baltic states' manufacturing sector and comparatively analyse the results. To achieve this, first, the growth rate of value added and its main contributors, namely hours worked and the growth rate of labour productivity, have been determined. Second, the main contributors to the growth rate of labour productivity, namely the contributions of labour composition, capital, and total factor productivity (TFP), have been established. Last, following the results, the relevant comparative analysis of newly derived indicators in the manufacturing sector has been accomplished, and conclusions have been presented. This paper used the growth accounting research methodology. Research limitations: the research was performed through the primary sources of growth approach, that is, only those determinants that remain important are incorporated in the model. Practical implications: the newly derived contributors to the growth rate of labour productivity reveal actual growth sources targeted to derive conclusions. The latter could be relevant for policy recommendations at both the national (e. g. guidelines for governmental policies for the selected economies) and the international (e.g., guidelines for EU policy and acts) levels. Originality and value: the novelty of the present study lies in the fact that the growth accounting method had not previously been applied in the manufacturing sector for the Baltic states. KEYWORDS: growth rate, value-added, labour productivity, hours worked, labour composition, capital

Based on two samples: 1) 1830 surviving SMEs; and 2) 406 non-surviving SMEs, this paper contributes to the literature on SME growth, checking the differences between the growth determinants of surviving SMEs and non-surviving SMEs. The multiple empirical evidence obtained allows us to conclude that there are significant differences in the relationships between determinants and growth in surviving and non-surviving SMEs: 1) Gibrat`s Law is rejected in the context of surviving SMEs, but it is not in that of non-surviving SMEs; 2) in surviving SMEs, age is a restrictive determinant of growth, with R&D expenditure, debt, government subsidies and labour productivity being determinants stimulating growth, whereas in non-surviving SMEs, R&D expenditure and debt are restrictive determinants of growth, but age, government subsidies and labour productivity are neither positive nor restrictive determinants of growth; and 3) cash flow is a positive determinant of growth in both surviving and non-surviving SMEs, but it is of greater importance for the growth of non-surviving SMEs than for that of surviving SMEs. The empirical evidence obtained allows us to make suggestions to SME owners/managers and political decision-makers.

Using the Feasible Generalized Least Squares econometric method, the paper analyzes the impact of climate change on economic growth in Vietnam's coastal South Central region over the period of 2006–2015. The results indicate that, after controlling for the main determinants in the growth model, the climate change with various proxies has a significantly negative impact on provinces' economic growth in the region. In particular, local institutions not only increase economic growth, but also reduce the negative impact of climate change on economic growth as well. These results suggest some policy implications aimed at boosting the process of transforming the economic growth model for the coastal region adapting to climate change. JEL codes: F21, F23, E22

The Paraguayan economy did not suffer debt crises in the eighties and had significant growth rates in the second half on the seventies, but poverty remained a problem. Understanding the performance and spatial distribution of poverty and inequality over a period of more than ten years can shed new light on structural causes behind what seems to be a low growth – high poverty – high inequality trap in Paraguay. How did poverty and inequality change during the 1990s. Did inequality reduce income growth? What were the growth determinants and what are the main forces driving inequality changes? These are the questions being answered in this book.

The Paraguayan economy did not suffer debt crises in the eighties and had significant growth rates in the second half on the seventies, but poverty remained a problem. Understanding the performance and spatial distribution of poverty and inequality over a period of more than ten years can shed new light on structural causes behind what seems to be a low growth - high poverty - high inequality trap in Paraguay. How did poverty and inequality change during the 1990s. Did inequality reduce income growth? What were the growth determinants and what are the main forces driving inequality changes? These are the questions being answered in this book.

Cover -- Acronyms -- Preface -- 1. Micro level estimation of income -- 1.1 Introduction -- 1.2 Methodology and Data -- 1.2.1 The Basic Methodology -- 1.2.2 The Income Model -- 1.2.3 The Implementation Procedure -- 1.2.4 Data Sources -- 1.3 Results -- 1.3.1 Regression Results -- 1.3.2 Poverty Estimates -- 1.3.3 Poverty and Inequality Maps -- 1.3.4 Pro-poor Growth Evidence -- 1.4 Discussion -- 1.5 Conclusions -- 2. Does Inequality Harm Income Mobility and Growth? -- 2.1 Introduction -- 2.2 Data: macro, micro and small area welfare estimates -- 2.3 Small area welfare estimation -- 2.4 The model -- 2.5 Estimation -- 2.6 Results -- 2.7 Discussion -- 2.8 Conclusions -- 3. Characterization of inequality changes through microeconometric decomposition -- 3.1 Introduction -- 3.2 Methodology -- 3.3 Income inequality in Paraguay: basic facts and sources of changes -- 3.3.1 Returns to education -- 3.3.2 Gender wage gap -- 3.3.3 Returns to experience -- 3.3.4 Unobservable Factors -- 3.3.5 Hours of work -- 3.3.6 Labour market participation -- 3.3.7 Education -- 3.4 Estimation strategy -- 3.5 Results -- 3.6 Discussion -- 3.7 Conclusions -- A: Annex to Chapter 1 -- B: Annex to Chapter 2 -- Bibliography.

This work aims to establish if the unemployment rate in Colombia is determined by expected inflation and the rate of economic growth, between 2001 and 2009, assuming that economic agents have adaptive expectations, in order to determine if there is a contradistinction on the economical policy objectives, towards demonstrating if the Phillips curve is inverse or not. On the other, it analyzes if economic growth causes lower unemployment rates, testing Okun's Law. It were used time series quarterized, where the main source of the database was Dane information, using the methodology of Johansen cointegration, estimating a vector error correction model and impulse response functions. The results show that the decreasement of unemployment rate is higher when there are increases on inflation expectation, than when there are increases on the economic growth rate ; Este documento pretende establecer si la tasa de desempleo en Colombia es explicada por la inflación esperada y por la tasa de crecimiento económico para los años comprendidos entre 2001 y 2009, suponiendo que los agentes económicos tienen expectativas adaptativas. Por otra parte, se intenta determinar si el crecimiento económico causa menores tasas de desempleo, comprobando así la Ley de Okun. Se utilizaron series de tiempo trimestralizadas del DANE, usando la metodología de la cointegración de Johansen (1995), estimando un vector de corrección de error y funciones de impulso-respuesta. Los resultados muestran que la tasa de desempleo para el periodo analizado disminuye si se incrementan las expectativas de inflación más que si se aumenta la tasa de crecimiento económico

Economic growth is a key point of macroeconomic policy and is the subject of constant attention and debate by professional public and policy makers. Theoretical and empirical research indicates differences in the level and direction of determinants' influence on the growth rate. The main goal of our article is to construct a model of economic growth determinants in South-East European countries. We used an unbalanced panel of 12 selected SEE countries over the period 2006–2019. Our empirical findings have shown that the most robust results can be obtained using a two-step generalized method of moments (GMM) model with dummy variable. In our dynamic model, we found that trade openness and gross fixed capital formation have a positive impact on economic growth, while government expenditures negatively determine economic growth. Gross fixed capital formation has the greatest positive impact on economic growth, while government expenditure has the greatest negative impact.