A matched employer-employee panel data set for Austria: 2002-2005

"Verknüpfte Arbeitgeber-Arbeitnehmer (Panel-) Datensätze gewinnen in der Analyse von Arbeitsmärkten zunehmend an Bedeutung. In Zusammenarbeit mit Statistik Austria haben wir den Aufbau eines verknüpften Arbeitgeber-Arbeitnehmer Panel-Datensatzes für Österreich über die Jahre 2002 bis 2005 initiiert. Das Ziel dieses Artikels ist es, diesen Datensatz einem größeren Publikum gegenüber bekannt zu machen. Zunächst stellen wir dessen Aufbau vor, wobei wir explizit sowohl auf die zugrunde liegenden Datenquellen als auch die Verknüpfungsprozedur eingehen. In einem weiteren Schritt präsentieren wir deskriptive Statistiken der im Datensatz enthaltenen Kernvariablen. Zu diesem Zweck betrachten wir drei unterschiedliche Analyseebenen: die Stichprobe als Ganzes, die Firmenebene sowie das einzelne Individuum." (Autorenreferat)"Matched employer-employee (panel) data sets are gaining increasing importance in the analysis of labour markets. In collaboration with Statistics Austria we recently initiated the set up of a matched employer-employee panel data set for Austria, which covers the years 2002-2005. The aim of the paper is to introduce the data set to a broader audience. We first present the set up of the panel data, indicating in more detail the data sources and matching procedure underlying the matched employer-employee data set for Austria. In a second step we show descriptive statistics of the main variables included in our data set. These various statistics encompass three levels of analysis: the aggregate level (i.e. the entire sample), firm level and individual (employee) level." (author's abstract

Measuring and explaining productivity growth of renewable energy producers: An empirical study of Austrian biogas plants.

This study explores productivity growth for a group of 65 Austrian biogas plants from 2006 to 2014 using Data Envelopment Analysis. The sample covers about 25 % of the installed electric capacity of Austrian biogas plants. Productivity growth is measured by calculating the Malmquist productivity index, and the contributions of technical change, efficiency change and scale change to productivity growth are isolated. Average annual productivity growth between 2006 and 2014 is 1.1 %. The decomposition of the Malmquist index shows that the annual scale change, technical change, and efficiency change for the average plant is 0.6 %, 0.3 % and 0.3 %, respectively. Those results indicate that the exploitation of returns to scale is a major driver of productivity growth in the Austrian biogas sector. However, there is a large variation in productivity growth across biogas plants. A second-stage regression analysis identifies important determinants of productivity growth. The results show that i) the exploitation of returns to scale as well as changes in ii) output diversification iii) capital intensity, iv) capacity utilization and v) feedstock prices are positively associated with productivity growth

Measuring and explaining productivity growth of renewable energy producers: An empirical study of Austrian biogas plants.

This study explores productivity growth for a group of 65 Austrian biogas plants from 2006 to 2014 using Data Envelopment Analysis. The sample covers about 25 % of the installed electric capacity of Austrian biogas plants. Productivity growth is measured by calculating the Malmquist productivity index, and the contributions of technical change, efficiency change and scale change to productivity growth are isolated. Average annual productivity growth between 2006 and 2014 is 1.1 %. The decomposition of the Malmquist index shows that the annual scale change, technical change, and efficiency change for the average plant is 0.6 %, 0.3 % and 0.3 %, respectively. Those results indicate that the exploitation of returns to scale is a major driver of productivity growth in the Austrian biogas sector. However, there is a large variation in productivity growth across biogas plants. A second-stage regression analysis identifies important determinants of productivity growth. The results show that i) the exploitation of returns to scale as well as changes in ii) output diversification iii) capital intensity, iv) capacity utilization and v) feedstock prices are positively associated with productivity growth

Price Competitiveness in the European Monetary Union: A Decomposition of Inflation Differentials based on the Leontief Input-Output Price Model for the Period 2000 to 2014

This paper studies the persistent producer price inflation differentials within the European Monetary Union. By applying a decomposition procedure within the input-output framework, the drivers of sectoral producer price inflation in a representative sample of member states are re-vealed. We find that in the pre-crisis period (2001-2008) the inflation differentials in manufactur-ing and market services of all countries vis-à-vis Germany were consistently positive resulting in a loss of price competitiveness for all economies. Manufacturing and market service sectors of many countries continued to lose price competitiveness, though to a lesser extent, also during the crisis period (2009-2014). We observe that differences in unit labour cost developments across countries constitute an important driver, especially in the pre-crisis period. Other drivers, such as import costs, intermediate input costs and operating surpluses also contribute, in particular dur¬ing the crisis period

Economic drivers of greenhouse gas-emissions in small open economies: A hierarchical structural decomposition analysis

The Paris agreement has prescribed strict Greenhouse Gas (GHG) reduction targets for participating countries. Implementation of climate protection policies is challenging, especially if the economy is export driven. We introduce a hierarchical structural decomposition model in order to investigate the effects of exports, imports, economic structure, consumption patterns, consumption level, outsourcing and insourcing on national GHG emissions. This model is applied to the data of national environmental accounts and to a harmonized and price-deflated series of national input-output tables of Austria for the years 1995, 2000, 2005 and 2010. Over the whole time period, the results indicate that the final demand effect was the main driver of GHG emissions, with exports as most important factor. Surprisingly, emission intensity contributed to an increase of GHG emissions during the period 2000-2005 as well, mostly due to increasing emission intensity in the transport sector

Economy 4.0: Employment effects by occupation, industry, and gender

The aim of this study is to investigate how the diffusion of the new digital technologies (Economy 4.0-technologies) effects the magnitude and composition of employment in Austria. For this purpose, an input-output framework is adopted taking into account direct as well as indirect effects of the new technologies by industry, occupation and gender. These employment effects are estimated as the difference between a base economy (as represented by the most recent Austrian input-output table) and the same economy after an assumed 10-year transformation period with the introduction of new production technologies and devel-opment of new products for final demand. Based on substitution potentials estimated on de-tailed occupational level available from previous research, we model the changes in labour productivity. Combining two different scenarios of labour productivity change with two dif-ferent assumptions about collective wage bargaining outcomes gives us four possible scenari¬os of macroeconomic paths of Economy 4.0. The results show that due to Economy 4.0 dur¬ing the next 10 years job displacement will probably be greater than job creation and aggre¬gate employment will decline by 0.80% to 4.81% relative to total present employment. Fur-thermore, the results indicate that occupations gaining in employment are highly skilled while the occupations losing in employment are medium-skilled. Hereby, the female workers are adversely affected in terms of employment and labour income

Economic drivers of greenhouse gas-emissions in small open economies: A hierarchical structural decomposition analysis

The Paris agreement has prescribed strict Greenhouse Gas (GHG) reduction targets for participating countries. Implementation of climate protection policies is challenging, especially if the economy is export driven. We introduce a hierarchical structural decomposition model in order to investigate the effects of exports, imports, economic structure, consumption patterns, consumption level, outsourcing and insourcing on national GHG emissions. This model is applied to the data of national environmental accounts and to a harmonized and price-deflated series of national input-output tables of Austria for the years 1995, 2000, 2005 and 2010. Over the whole time period, the results indicate that the final demand effect was the main driver of GHG emissions, with exports as most important factor. Surprisingly, emission intensity contributed to an increase of GHG emissions during the period 2000-2005 as well, mostly due to increasing emission intensity in the transport sector

How far away are the CEECs from the EU economic standards? A data envelopment analysis of the economic performance of the CEECs.

In October 1999 the European Commission published the second progress report on the state of convergence of the Central- and Eastern European candidate countries (CEECs). The report encompasses an assessment, which is based on the three Copenhagen criteria. From an economic point of view, a country must have a functioning market economy and be able to withstand the competition on the European single market. In this paper we present a synthetic performance measure which helps to assess the economic preparedness of the ten Central and Eastern European Countries (CEECs) to become members of the European Union (EU). With the aid of the Data Envelopment Analysis (DEA) we construct a best practice frontier, which is supported by the best performing EU-countries and which serves as a benchmark for the candidate countries. The preparedness of any CEEC is measured as the relative distance to this frontier. The results confirm that the macroeconomic performance of most of the CEECs lies far behind the EU standards, in foreign trade some of the CEECs already perform better than some EU countries. Interestingly, we find out that some CEECs are already better prepared for the EMU than many EU member states.Series: EI Working Papers / Europainstitu

Welfare implications of the EU's common organization of the market in bananas for EU Member States

The objective of this paper is to analyze the welfare effects of the European Banana Market Policy. Until 1993, EU countries had a wide variety of separate national policies, ranging from free trade (e.g. Germany) to heavily regulated markets (e.g. Spain, France). On 1 July 1993, the EU's common organization of the market in bananas came into force and established a combined quota-tariff regime with preferential access for ACP and EU suppliers. We estimate the resulting changes in the welfare of consumers, traders and the national governments for all member states of the European Union to identify the winners and losers of this change in the external trade policy. Over the period 1993 to 1998, the cumulated aggregate welfare loss of the consumers amounted to ECU 1408 mill, whereas the international banana traders gained ECU 558 mill. on the EU market. The welfare effect on the national budgets of the EU member states was also positive (ECU 783 mill.) due to higher tariff income. The resulting total deadweight loss of the European Union amounted to ECU 68 mill. As regards the distribution of the welfare effects, the former free trade countries lost welfare, whereas the formerly severely regulated countries gained. In absolute terms the biggest loser of the regime shift is Germany, the biggest winner is France. (authors' abstract)Series: EI Working Papers / Europainstitu