All articles by Priya Chetty

Auto regressive distributed lag model (ARDL) and its advantages

Auto regressive Distributed Lag Models (ARDL) model plays a vital role when comes a need to analyze a  economic scenario. In an economy, change in any economic variables may bring change in another economic variables beyond the time. Read more »

Building univariate ARIMA model for time series analysis in STATA

Autoregressive Integrated Moving Average (ARIMA) is popularly known as Box-Jenkins method. The emphasis of this method is on analyzing the probabilistic or stochastic properties of a single time series. Unlike regression models where Y is explained by X1 X2….XN regressor (like the introductory case where GDP is explained by GFC and PFC), ARIMA allows Y (GDP) to be explained by its own past or lagged values. ARIMA is performed on a single time series. Read more »

Getting acquainted with neural network analysis

Neural network, popularly known as Artificial Neural Network (ANN) is an information processing system with a large number of nodes and connections as part of a structure which helps in processing complex information. It is influenced by biological human nervous system which consists of a huge number of neurons connected to each other and work together to find solutions for different specified problems. Similarly, ANN sends different responses from different neurons or nodes to the output layer and this outer layer behaves and takes actions accordingly. Read more »

Performing Canonical Correlation Analysis (CCA)

Until recently, Karl Pearson Correlation analysis was one of the most popular methods to measure linear association between two or more than two variables in a data set. For example, establishing the Karl Pearson Correlation between X variable and Y variable, where both variables belong to a single data set. Canonical Correlation Analysis (CCA), on the other hand, helps measure the correlation among variables which are in different datasets. Read more »

Solving complicated problems with decision tree

A decision tree is a graphical representation of possible solutions to a problem based on given conditions. It is called a tree because diagrammatically it starts with a single box (target variable) and ends up in numerous branches and roots (numerous solutions). It is a type of supervised learning algorithm that have  target variables and in order to select solutions it creates classifications. Based on classifications, however, it is applied on both categorical and continuous variables. Read more »

Rules governing non-banking financial companies (NBFC) in India’s real estate sector

Traditionally, India has had a bank dominated financial sector. Even so, there have always been Non-Banking Financial Companies (NBFC) to provide finance to mainly unorganized markets. NBFC have continued to complement banks in providing infrastructure finance. When it comes to providing medium-term capital, they enjoy more flexibility than banks, which gives them a competitive edge over banks. Read more »

Meta-analysis for one group

The previous article, explained how to enter data for performing meta-analysis of the studies reporting comparison data. Therefore the present article will explain the data entry methodology, for performing meta-analysis on the outcomes of studies having a single group. For this purpose, the single group of patients who were administered drug treatment will be taken into consideration. Read more »

Credit risk faced by microfinance institutions (MFI) in India

The microfinance industry of India is a major enabler of financial inclusion in the country. It has also been a blessing for small scale industries which act as an important source of income for a significant population. However, microfinance institutions (MFI) are faced with many problems which restrict their potential. These issues, mainly associated with credit risk, are discussed here. Read more »

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