The Impact of Computers on Productivity in the Trade Sector: Explorations with Dutch Microdata

Trends in productivity, labor, and investment in the retail and wholesale trade sectors for the Netherlands in the 1988-94 period are examined. The analysis is based on a longitudinally linked panel of firms from the annual survey of Production Statistics collected by Statistics Netherlands (CBS). We find that computer investments have a positive impact on productivity and that the productivity impact of computers is greater in retail than in wholesale trade. There are a number of possible reasons for this finding, including greater penetration of computers in wholesale trade and differences in the way computers are deployed in the two sectors. Contrary to studies in the U.S., however, the impact of computer capital is about the same as other forms of capital. Differences in empirical specifications arising from the absence of data on capital suggest some caution with respect to this conclusion. We also find increased use of "flexible" employment practices, particularly among retail firms, and these appear related to computer use. As expected the measured impacts of computers on productivity are quite sensitive to the particular deflator used for computer equipment.

Regional Labour Productivity in The Netherlands - Diversification and Agglomeration Economies

This paper studies the extent to which diversification and agglomeration effects account for regional differences in labour productivity levels and labour productivity growth. Using a large set of regional data for The Netherlands for 40 labour market areas between 1990-2001 we find that roughly 60% of the explained variation in regional productivity differences and 55% of the regional growth differences can be attributed to indicators of diversification and agglomeration effects. A sensitivity analysis shows that these effects are fairly robust.

Regional labour market dynamics in The Netherlands

This paper analyses the response of the Dutch labour market to a regional labour demand shock. European-wide studies and US labour market studies found that in Europe adjustment to such a shock runs primarily through changes in participation, while in the US this is through migration of workers. Another striking difference is that the admustment process in the US takes places a much higher speed than in regions in European countries The main explanation for this phenomenon is the rigid labour market in Europe, against the flexible labour market in the US, which is expressed by the fact that spatial mobility among US workers is much higher than among European workers. A similar approach to the Dutch labour market shows that adjustment to labour demand shocks is primarily through changes in participation. In that sense it fits the European picture. As far as the speed of adjustment to a shock is concerned, the Dutch labour market seems more in line with American than with European levels. A disaggregate analysis shows that particularly the response of the northern labour market stands out. Adjustment to a shock is absorbed faster than in other Dutch regions. Furthermore, unemployment and migration are more important as absorption channels in the North than in the other regions.

Regional Differences in Productivity Growth in the Netherlands - an Industry-level Growth Accounting

Main point in the current European policy debate is to find instruments that stimulate the growth rate of labour productivity. The reason for this is a persistent slowdown in labour productivity growth in European countries and an increasing gap in growth rates between the USA and Europe starting in the second half of the 1990’s. Labour productivity in the US is nowadays at a much steeper growth path than in Europe. What is the reason for this increasing gap between Europe and the USA? This is an important question in order to assess the measures proposed in the Lisbon Agreement by the European Union (EU) to become the world’s most competitive and dynamic knowledge-based economy in 2010. With increasing globalisation and deregulation of international markets, productivity growth is the tool to enhance competitiveness. Therefore instruments are sought that will get the productivity growth rate in European countries back on track. One of the main explanatory factors for productivity growth is the production, use and diffusion of information and communication technology (ICT). Inklaar et al. (2003) show, however, that the main source for the European slowdown in productivity growth is not so much lagging IT use, but a deceleration of non-ICT capital deepening (i.e. lagging increase of non-ICT capital per hour worked) and, in contrast to the US, a lack of acceleration of TFP growth. TFP growth is the part of productivity growth that cannot be attributed to an increase in the capital stock per hour worked, where capital is usually subdivided in ICT capital and non-ICT capital. Daveri (2004), who applies a more rigorous definition of ICT using and ICT producing industries, by and large corroborates these results. The deceleration of non-ICT capital deepening of the nineties in Europe has coincided with a sharp rise in employment. Non-ICT capital deepening, or the growth of non-IT capital per hour worked, is clearly related to the growth rates of the price of both inputs. Faster wage growth increases non-ICT capital deepening because capital will substitute labour. An increase in the ‘price’ of non-ICT-capital, on the other hand, makes capital more expensive and leads to deceleration of non-ICT capital deepening. Inklaar et al. (2003), however, show that the impact of growth rates of wage and rental prices on non-ICT capital deepening is much stronger for the US than Europe. The small effect of wage growth in European countries implies that wage moderation might be an important reason for the slowdown of non-ICT capital deepening. Labour productivity growth in The Netherlands is at a persistently lower growth path than the European average. Since The Netherlands has been champion in wage moderation in the past decades, a natural question is whether this has led to an even slower non-ICT capital deepening than Europe or that other mechanisms have instead caused the Dutch slowdown of productivity growth. This issue will be addressed at a low spatial level: what is the reason for the Dutch slowdown, are there regions that have contributed more to the lagging productivity growth rate than others and which industries are responsible. This question will be answered using the growth accounting approach, which is also used to explain the widening of the productivity growth gap between Europe and the USA. Distinction can be made at the provincial level of The Netherlands between growth rates of value added in constant prices, number of hours worked, ICT and non-ICT capital services for eight aggregate industries. There is therefore sufficient detail to determine which industry in which province contributes positively or negatively to the lagging Dutch growth performance of the late 1990’s. This issue is useful from both an academic and a policy perspective.

Regional differences in productivity growth in The Netherlands: an industry-level growth accounting

It is well known that the productivity growth in Europe is slowing down, against an increasing growth rate in the US. The Netherlands is one of countries in Europe with the lowest growth rates of productivity. This paper presents the results of a growth accounting exercise applied to regional industry data of The Netherlands between 1995-2002. We find that low productivity growth in The Netherlands is particularly situated in the economic core regions of the west and south and is caused by slow growth of MFP. Compared to the more peripheral regions, MFP-growth is lower in all industries, except social and non-market services. The high level of traffic congestion and relatively low labour effort in the core regions can explain part of this slow MFP-growth.

mgm: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data

We present the R-package mgm for the estimation of k-order Mixed Graphical Models (MGMs) and mixed Vector Autoregressive (mVAR) models in high-dimensional data. These are a useful extensions of graphical models for only one variable type, since data sets consisting of mixed types of variables (continuous, count, categorical) are ubiquitous. In addition, we allow to relax the stationarity assumption of both models by introducing time-varying versions MGMs and mVAR models based on a kernel weighting approach. Time-varying models offer a rich description of temporally evolving systems and allow to identify external influences on the model structure such as the impact of interventions. We provide the background of all implemented methods and provide fully reproducible examples that illustrate how to use the package

How do Dutch regional labour markets adjust to demand shocks?

This paper analyses the response of regional labour markets in The Netherlands to region specific labour demand shocks. Whereas previous studies analyse only average patterns of all regions in a country, this paper provides also a more in debt analysis of within country differences in labour market adjustment processes. Previous studies show remarkable differences in response between regions in European countries and regions in the United States. The analysis in the present paper shows that in Dutch regions the labour market adjusts to labour demand shocks primarily through changes in participation. In that sense it fits the European picture. As far as the speed of adjustment to a shock is concerned, the Dutch labour market seems more in line with American than with European levels. A spatial disaggregated analysis shows remarkable differences between regions within the Netherlands. In particular the response of the regions in the northern part of the country stands out. First, adjustment to a shock is absorbed much faster than in other Dutch regions. Second, the shock is absorbed more through changes in unemployment than changes in participation.

Gender-specific dynamics in working hours

Abstract Gender-specific dynamics in working hours ERSA Barcelona 2011 The Dutch are part-time working champions of the world, not just because the majority of women work part-time, also a growing number of men are working part-time. However, with the aging of the population there is an increasing threat to current welfare levels. The aim of this paper is to assess the possibilities of a rise in wealth through a change in (the trend of) working hours. For the analysis we have created a unique data base which includes workers that have occupied the same job in the period 2003-2005. This means we abstain from dynamics in jobs, (i.e. job finders, job switchers, job losers), which can partly be attributed to changes in participation. Instead we focus completely at working hours of a given job. The analysis is comprised of two parts, first we analyse factors determine the actual number of hours worked for both female and male occupied jobs. Second, we analyse the dynamics in working hours of a given job using a bivariate probit estimation with selection. This model takes into account what factors determine if a person does or does not change working hours and subsequently examines which factors determine whether this change is an increase or a decrease in working hours. Women more frequently change their working hours than men and both rather decrease than increase their working hours. Changes in work situation and household situation are important determinants of changes in working hours, for women also changes in residential context play a role. A decrease in hourly wage and a relative decrease in the burden of taking care of small children are important determinants of increasing working hours, for both men and women. Although men only decrease their working hours after the birth of the first child.

Variatie in broedomstandigheden geeft variatie in broeduitkomst en kuikenkwaliteit

De combinatie van de variatie in broedomstandigheden met de gevoeligheid van eieren van verschillende rassen en merken bij diverse leeftijden voor afwijkende broedcondities, kan verschillen in broeduitkomsten en kuikenkwaliteit verklaren