Foreign direct investment and transition economies: empirical evidence from a panel data estimator

This paper identifies the factors that determine FDI inflows in the former socialist countries of Eastern and Central Europe. In our analysis, FDI inflows are modeled as a function of the market size (i.e., real GDP), inflation, the current account balance, the real exchange rate, openness and government regulation for the host country. Using data from 1995 to 2004, a panel data estimator suggests that the real exchange rate, openness of the economy and deregulation are the primary factors determining FDI inflows in these countries.

Foreign Aid, FDI and Economic Growth in East European Countries

This paper examines the effectiveness of foreign aid and foreign direct investment in the Czech Republic, Estonia, Hungary, Latvia, Lithuania and Poland. The model includes the labor force, capital stock, foreign aid and foreign direct investment, and is estimated using pooled annual time series data from 1993 to 2002. Before carrying out the estimation, the time series properties of the data are diagnosed and an error-correction model is developed and estimated using a fixed-effects estimator. The results indicate that an increase in the stock of domestic capital and inflow of foreign direct investment are significant factors that positively affect economic growth in these countries. Foreign aid did not seem to have any significant effect on real GDP.

Log Analysis and Anomaly Detection in Log Files with Natural Language Processing Techniques

Log analysis is a crucial aspect of maintaining and improving the performance, security, and reliability of modern computer systems. The increasing complexity of these systems along with the exponential growth of log data has driven the need for the development of more advanced techniques for understanding and analyzing logs. In this project, we propose a log management infrastructure with Elastic Stack for statistical analysis equipped with visualization features and natural language processing (NLP) based approaches for the process of log analysis and anomaly detection. We build upon a classification model with 4 different classes on a small sampled dataset to develop a proof-of-concept (POC) to validate that the proposed solution aligns with the problem statement. We then scale up the solution to the full dataset to develop anomaly detection in real-world syslog data generated in industrial settings. This enables faster and more effective decision-making which in turn frees the human workforce from the manual repetitive process of log inspection. First, raw textual and unstructured logs in various formats and from different sources such as Continuous Integration/Continuous Deployment (CI/CD) servers, ambulatory monitoring devices, and automated test builds are collected. Then, the obtained logs are preprocessed to clean, normalize, and tokenize into tokens. The tokenization is carried out using word and sub-word tokenization techniques to obtain word and sub-word tokens respectively. The tokens are then converted into meaningful numerical representations using static and contextual word embedding algorithms such as Word2Vec, BERT, and DistilBERT pretrained models to generate word embeddings. The word embeddings are thus fed into neural networks for the classification of log lines into designated labels. The experiments performed with the combination of DistilBERT embedding model and LSTM classifier network for logs generated from patient monitoring devices achieved an accuracy of 0.99 with macro-averaged precision of 0.96, recall of 0.93 and F1-score of 0.94 in a multi-label classification. The results showed promising signs towards the automation of log analysis of syslogs generated from test-builds and patient monitoring systems

Nepal and Bhutan: development strategies and growth

This paper has sought to examine the factors that have contributed to the economic growth of Nepal and Bhutan. After a brief discussion of the economy and growth strategy of each country, standard growth models for Nepal and Bhutan are developed and estimated. The results indicate that domestic capital has been a significant source of economic growth in Nepal whereas foreign aid has not had any appreciable effect on growth. The reverse is true for Bhutan

Foreign Aid, FDI and Economic Growth in East European Countries

This paper examines the effectiveness of foreign aid and foreign direct investment in the Czech Republic, Estonia, Hungary, Latvia, Lithuania and Poland. The model includes the labor force, capital stock, foreign aid and foreign direct investment, and is estimated using pooled annual time series data from 1993 to 2002. Before carrying out the estimation, the time series properties of the data are diagnosed and an error-correction model is developed and estimated using a fixed-effects estimator. The results indicate that an increase in the stock of domestic capital and inflow of foreign direct investment are significant factors that positively affect economic growth in these countries. Foreign aid did not seem to have any significant effect on real GDP

Exchange Rate Volatility And Foreign Direct Investment: Evidence From East Asian Countries

This paper uses panel data to examine the effect of exchange rate uncertainty on foreign direct investment in China, Indonesia, Malaysia, the Philippines, South Korea, and Thailand – countries that have continued to attract considerable foreign direct investment (FDI) inflows while also experiencing a great deal of volatility in exchange rates.  After establishing the stationarity of the data series, a panel cointegration test was conducted, following which an error correction model was developed and estimated using two sets of panel data.  The overall estimation results are consistent with theoretical predictions.  We find that exchange rate volatility has a favorable effect on foreign direct investment in our sample countries

Economics of fish production at Chitwan district, Nepal

A study was conducted in 2016 to analyze the economics of fish production at Chitwan District of Nepal. Three study sites: East, West and South part of Chitwan were selected purposively. A total of 90 households, 30 from each study site were selected randomly and were interviewed by using pre-tested semi structured questionnaire. Secondary data needed for the study were obtained from DADO, MOAD, NARC and other related organizations working on fisheries and aquaculture sector. Descriptive statistics and extended Cobb Douglas production function was used to accomplish the study objectives for which MS-Excel and SPSS 16 were used. The B/C ratio is obtained dividing the gross return by total variable cost incurred. The total cost of production per ha of the pond area was Rs. 743798 per year with 79 and 21 percent variable and fixed cost components, respectively. Feed cost (28 %) was largest cost item followed by cost for labour (25 %), fingerlings (10 %), maintenance (6 %), manure cum fertilizers (5 %), fuel cum energy (3 %) and limestone and others (2%). The average gross return and net profit realized per ha were Rs. 1223934 and Rs. 480135 respectively. The cost, return and profit were calculated to be highest for east Chitwan with highest B/C ratio followed by west Chitwan and south Chitwan. The B/C ratio for the district was found to be 1.63. The return to scale was found to be decreasing with value of 0.654 indicating that 1 percent increment in all the inputs included in the function will increase income by 0.654 percent. Production function analysis, including five variables, showed significant effect of human labour, fingerlings and fuel cum energy cost but feed and manure cum fertilizers cost were insignificant