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When country's home market is quite small, companies develop exports in order to achieve greater sales volume and profit. Export is one of the ways to survive and develop business for companies of small open-economy countries. Such a tendency especially became evident during economic decline, when consumption in home market shrank. Recent Lithuania's economic growth is based on increasing exports, as well. On the other hand, estimation of trade credit risk factors is getting more and more important for exporting companies as the most popular settlement mode in the world is trade on an open account. Exporters, aiming to be the first in rivalry struggle and make a contract with a customer, have to propose the most beneficial conditions to the customer they can, i.e. to provide the customer with a trade credit. Exporter, when providing a trade credit for a foreign customer, takes a risk to lose financial resources. Risk of provided trade credit is evaluated on purpose to avoid the risk, i.e. the factors determining credit non-repayment and factors envisaging the risk are identified. One of the main factors determining trade credit risk is customer's insolvency, therefore designing a model to evaluate trade credits risk factors it is essential to analyse what predicts customer's ability to repay the trade credit given. Two approaches may be found in literature: evaluation is based on the analysis of financial indicators or on the analysis of both financial and non-financial indicators. Usually only financial indicators are used. In a traditional credit analysis mainly a company's accounting data is used aiming to assess if the company is able to generate cash enough to meet its liabilities. The research done shows, however, financial assessment is insufficient and does not give complete view about a company's business. In literature researches are found to be aimed at choosing such non-financial indicators that would be able to predict a company's insolvency, though a systematic approach to the use of certain indicators is scarce, especially which of them should be used to evaluate foreign customer's reliability in the case of export. Providing a foreign customer with the credit, an exporter incurs impact of the foreign country environment forces, as well. This is true because, when an exporter provides a trade credit, crediting relations bind subjects from two different countries and those subjects are both affected by different countries' forces. Country risk evidences for the exporter as the customer is another country; here country risk is understood as the manifestation of forces that affect customer only in the home business environment (customer's home country). These forces may circumvent the exporter from getting repaid or affect customer in such a way that the latter will become insolvent.

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OECD industry classification distinguishes four industrial groups in the manufacturing industry: high-tech, medium high-tech, medium low-tech and low-tech. Low-tech industries are deemed to be those that add little value to a country's economy and are less competitive, though recent studies in different countries show that they may be innovative and knowledge intensive ones. In the paper we aim to show what role low-tech industries play in Lithuanian manufacturing industry and the economy. Therefore the main aim of the paper is to make a comparative analysis of Lithuanian industries' data and reveal low-tech's contribution to Lithuanian manufacturing sector and the economy. For the analysis we use data from the Lithuanian Department of Statistics (Statistics Lithuania) and other data bases for the year 2010-2011. We base the comparative data analysis of different industrial sectors mainly on the set of indicators proposed by Laestadius, Pedersen & Sandven (2006) and use additional one of orientation to export. The analysis showed that low-tech industries make a considerable contribution to Lithuanian manufacturing industry sector and is important to the whole economy, as well.

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