In this paper, we offer a unique firm-level view of the empirical regularities underlying the evolution of the Lithuanian economy over the period of 2000-2014. Employing a novel dataset, we investigate key distributional moments of real and financial variables of Lithuanian firms. We focus in particular on the issues related to productivity, firm birth and death and the associated employment creation and destruction across firm sizes, industry classification and trade status (exporting vs. non-exporting). We refrain from any structural modelling attempt in order to map out the key economic processes across industries and selected firm characteristics. Nevertheless, existing theoretical and empirical findings guide our analysis and the selection of the main variables to investigate. We uncover similar regularities as already highlighted in the literature: trade participation and firm productivity are strongly positively linked, the 2008 recession has had a cleansing effect on the non-tradable sector, firm birth (death) is highly pro (counter)-cyclical. The richness of the dataset allows us to produce additional insights: for example, we observe an increasing share of exporting but a constant share of importing firms since 2000.

We investigate the structural disturbances underlying the business cycle in Lithuania in the bivariate time series framework. In the structural VAR model constructed productivity, hours of work and output fluctuations over the business cycle are composed of technology and non-technology shocks. We find that a technology shock has a persistent positive effect on all three variables. Non-technology disturbance has a long-term impact on working hours and output, but it has a negligible short-run effect on productivity.Differently from Gali (1999), the study has revealed no significant correlation between productivity and working hours under the effects of technology shocks on Lithuanian data. In contrast with the results of developed countries, non-technology shocks result in a significant negative correlation between the working hours and labour productivity in Lithuania.Historical decomposition of output, productivity and working hours series allows distinguishing four different episodes of Lithuanian economy during the analysed timeline. In 1999, negative technology shocks played the biggest role in pushing the output down. During the period 2001–2004, the real GDP growth was supported by productivity increase due to technology shocks; in 2005–2008, non-technology shocks and the higher working hours were fuelling output growth together with a positive impact of the technology shock on productivity growth. Finally, 2008–2011 is the period of negative technology and non-technology shocks.

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