Publications

This paper analyzes the firm’s choice between subsidy support and loan support during the COVID-19 crisis and explores the implications of this choice on firms’ employment growth. We compile a novel micro-level dataset of Lithuanian firms’ balance sheet data and government support records during the pandemic period. We use the dataset to provide a set of stylized facts, categorizing the variety of enacted support policies and tracking aid distribution patterns. We show that larger firms were more likely to choose loans over subsidies. This result cannot be fully explained by policy eligibility criteria and the severity of the pandemic shock, suggesting that firm characteristics played a significant role. Finally, we show that the type of support has implications for firms’ outcomes – subsidy-recipient firms experienced higher employment growth compared to loan-recipient firms.

The ‘aid conditionality’ hypothesis as advocated in the literature suggests that aid is effective in augmenting growth only in the presence of a sound policy environment. This hypothesis was so influential that its policy recommendation, to provide aid conditional upon recipient domestic policies, is currently the dominant ODA allocation criterion. However non-economic dimensions of development (political and institutional) are increasingly seen as fundamental. For this reason, this paper focuses on the linkage between aid and a noneconomic factor like Human Rights (reflecting repression and corruption) as a measure of aid effectiveness, in explaining growth outcomes across 42 Least Developed economies. We find that countries with better human rights experience positive growth from aid receipts, signifying the role of strong institutions and good governance in enabling more effective use of aid. The paper thus concludes that the measurement and monitoring of human rights provision is a useful tool in gauging the likely effectiveness of foreign aid.

Keywords: Human rights, aid effectiveness, corruption, oligarchy.
JEL Classification: F35, P16, P40, O19.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

ABSTRACT

This paper provides empirical evidence on how the aftermath of the 2008 crisis affected firm productivity in the UK, taking account of the cohort effect of firms established after 2008. We test this using firm-specific and time-varying credit scores to capture firms’ ability to access credit. To overcome the identification problem, a matched sample based on firm’s credit score, firm age, size and ownership status is used by undertaking the propensity score matching approach. While we find evidence that smaller firm size and changes in credit conditions affect productivity, about half of the difference in productivity remains unexplained. We extend the matching analysis to examine sectors and cohorts, and find that, during 2011-2016, the low productivity is driven primarily by newer firms operating in the services sector, rather than in manufacturing. Within services, the underlying productivity puzzle is driven by a cessation of growth in high-productivity financial services, while abundant labour supply has led to a ‘levelling down’ of performance of newer firms in the rest of services, in line with relatively low productivity manufacturing.

Keywords: Total Factor Productivity, Cohort, Crisis, Firm Survival, Credit Score.
JEL Classification: E00, D24, E30, G21

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.