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In present days, the cultivation of land at the tail end has reduced, reasons being - insufficient irrigation water and inefficient distribution of canal water to the tail ends. As a result, farmers of Peddapatnam village are unable to carry out cultivation satisfactorily. This study is carried out to address this problem and to provide remedies. Peddapatnam canal is selected as the study area in the present paper. This canal (16°21'35.89"N, 81°15'42.82"E - 16°19'24.92"N, 81°19'46.10"E) is a branch canal of Bantumilli main canal (16°20'37.00"N, 81°3'28.61"E - 16°23'52.02"N, 81°26'13.82"E), located in Krishna district of the Andhra Pradesh State. The water from the canal is the only source for cultivation and groundwater is unsuitable as it contains a large amount of salts. Firstly, the current flows of the Bantumilli canal are found and the total cultivable land in the purview of the canal is determined. Later, a topographic survey is conducted and the longitudinal profile of the canal is drawn. Farmers and irrigation experts (who are familiar with the study area) were interviewed to know the causes and find possible remedies for the problems encountered. The problems identified are, viz., (i) Low maintenance of the canal (ii) Canal being unlined (iii) Absence of protection of side banks (iv) Damage caused by animal movements (v) Siltation (vi) Non-cooperation of some influential farmers. Seepage and evapo-transpiration have also greatly affected the efficiency of canal distribution. Based on the above observations, two recommendations are proposed, viz., (i) Construction of a retaining wall or (ii) Construction of a canal lining. Additionally, it is recommended to install solar panels along the canal to address the power shortage problem of that area. An income of 30 million Indian rupees is realized due to the installation of a canal-top solar plant, for the cash-strapped region under study. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between the USD/INR implied volatility and future realized volatility by using non-overlapping monthly volatility data from April 2005 to March 2017. The empirical results suggest that the USD/INR implied volatility is biased, yet a better predictor of future realized volatility of the exchange rate than historical volatility and GARCH forecast. The out-of-sample forecast also shows that implied volatility outperforms both historical volatility and GARCH forecast in predicting future realized volatility. The implied volatility is found to be an efficient predictor vis-à-vis historical volatility as it subsumes all the information content of the historical volatility about future realized volatility. However, the GARCH forecast contains some incremental information about future realized volatility beyond the information contained in the implied volatility, though the predictive power of implied volatility remains higher than the GARCH forecast. [ABSTRACT FROM AUTHOR]

Foreign exchange risk management is a new challenging area. After globalization, the perfection in exchange rate forecasting is very essential for hedging decisions. In this paper, an attempt has been made to estimate the parameters of Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and apply them to simulate and predict the rupee/US dollar exchange rates. The emphasis of these methods is not on constructing single equation or simultaneousequation models but on analyzing the probabilistic or stochastic properties of economic time series on their own under the philosophy of letting the data speak for themselves. As a matter of fact, many econometric time series exhibit periods of unusually large volatility, followed by periods of relative tranquility. In such circumstances, the assumption of homoscedasticity is inappropriate. It is a particular kind of the Heteroscedasticity in which the variance of the regression error depends on the volatility of the errors in the recent past. Engle suggested the use of Autoregressive Conditional Heteroscedasticity (ARCH) model to take care of such Heteroscedasticity in order to raise the efficiency of forecasts. Many of the lagged values of unconditional error variance can be replaced with one or two lagged values of conditional error variance. This leads to the GARCH model. The main objective of this paper is to study the GARCH-based minimum mean squared error ARIMA forecast for rupee/dollar exchange rate and draw a comparison between ARIMA, GARCH-based ARIMA and RBI forecasting. [ABSTRACT FROM AUTHOR]

The paper is concerned with time series modelling of foreign exchange rate of an important emerging economy, viz., India, with due consideration to possible sources of misspecification of the conditional mean like serial correlation, parameter instability, omitted time series variables and nonlinear dependences. Since structural change is pervasive in economic time series relationships, the paper first studies this aspect of the exchange rate series in detail and finds the existence of four structural breaks. Accordingly, the entire sample period is divided into five sub-periods of stable parameters each, and then the appropriate mean specification for each of these sub-periods is determined by incorporating functions of recursive residuals. Thereafter, the GARCH and EGARCH models are considered to capture the volatility contained in the data. The estimated models thus obtained suggest that return on Indian exchange rate series is marked by instabilities and that the appropriate volatility model is EGARCH. Further, out-of-sample forecasting performance of the model has been studied by standard forecasting criteria, and then compared with that of an AR model only to find that the findings are quite favorable for the former. [ABSTRACT FROM AUTHOR]

Objective: Paper currency notes are found to contaminate with microbes and the dissemination of antibiotic resistance is a global health problem. The aim of this study was to evaluate the prevalence of multi-drug resistant bacteria in the Indian currency notes. Study design: For this study, the Indian currency notes (rupee notes 10, 20 and 50) were collected from Tamil Nadu, Karnataka, West Bengal, Assam, New Delhi and Gujarat using random sampling technique. The sampling was categorised into; category 1: local markets, beggars, street vendors, conductors, hospitals and Category 2: supermarkets, banks including ATM machines, and hotels. Method: Spread plate technique, specific media and biochemical tests were used for the bacterial isolation and identification. Identification of multiple drug resistance, PCR-based screening of resistance genes and conjugation studies were performed. Results: The total of 75 bacteria was isolated including Bacillus sp., Streptococcus sp., Staphylococcus sp., Staphylococcus aureus, Escherichia coli, Klebsiella sp., Pseudomonas sp. and Salmonella sp. Multi-drug resistance was observed in 32/75 (43%) isolates and the prevalence of 25% ertapenem-resistant and 21% cefotaxime resistant bacteria was observed. The presence of blaCTX-M-9 in three isolates such as E. coli (two) and Klebsiella sp. was screened and E. coli isolates were found to involve in conjugating its resistance to E. coli AB1157. Conclusions: Our study showed the prevalence of multiple drug resistant bacteria in the Indian currency notes and also in disseminating its resistance. [ABSTRACT FROM AUTHOR]

The demonetization is that the method of withdrawal of a specific style of currency from circulation. Demonetization becomes necessary whenever there's an amendment within the national currency. The recent unit of currency should be retrieved and replaced with a replacement currency unit. It involves either introducing new notes or coins of a similar denomination or fully substitution the recent denominations with the new denomination that is typically applied as ambush on the black market. In India demonetization has occurred thrice. The primary was on 12/1/1946 (Saturday), second on 16/1/1978 (Monday) and therefore the third was on 8/11/2016 (Tuesday). In the present paper, there is a survey on the effects of demonetization on the various economic factors, views of national and international economists including media and the previous demonetization in other parts of the world with their side effects. Thus, the findings of this study reveal that, India can deliver the goods a major growth by adapting the demonetization strategy and it'll produce an enormous positive impact on the whole economy in an exceedingly long-standing time. [ABSTRACT FROM AUTHOR]

India and China are the two emerging economies of the world. They are the two most populous countries in the world who together account for more than a third of the world's total population. A descriptive research study has been carried out for investigating the Gross Domestic Product of India and China in nominal and purchasing power parity basis. It also compares per capita gross domestic product and GDP growth rate of India and China. It also investigates the trends in the value of Chinese Yuan Renminbi (CNY) with Indian Rupee (INR). This paper also exhibits the market share in Foreign Direct Investment in Asia Pacific region in 2015. The dramatic rise not only enabled socioeconomic upsurge of India and China but it also reshaped the regional and global trade trends. India replaced China as leading recipient of capital investment in Asia-Pacific with announced FDI of $63bn, as well as an 8 per cent increase in project numbers to 697. India faced various structural bottlenecks including delays in project approval, ill-targeted subsidies, a low manufacturing base and low agricultural productivity, difficulty in land acquisition, weak transportation and power networks, strict labour regulations and skill mismatches. [ABSTRACT FROM AUTHOR]

The long run dynamics of Indian foreign exchange market with respect to Indian Rupee-US Dollar spot rate can be attributed to interplay of several domestic, foreign and global factors. This paper attempts to identifies whether there exists any long term equilibrium relationship among macroeconomic variables of India and US, Indian Rupee-Euro spot rate, Indian Rupee-Yen spot rate, Indian Rupee- UK Pound spot rate and Indian Rupee-US Dollar spot rate. Time series analysis has been undertaken for ten year period of April, 2005--March, 2015 using monthly data of these variables. The variables considered are money stock (India and US), nominal long run bond yield (India and US), commodity price levels (India and US), stock prices (India and US), forward premium in Indian rupee-US dollar forward market, foreign exchange reserves with Reserve Bank of India, Indian rupee-euro spot rate, Indian rupee-British pound spot rate and Indian rupee-Japanese yen spot rate. Johansen's co-integration analysis indicates that all Indian and US macroeconomic variables and other currency pairs of rupee are in a long run relationship with rupee-dollar spot rate. [ABSTRACT FROM AUTHOR]

There is a vast literature on asset return predictability in a linear regression framework. However, there is increasing evidence that asset returns may be better characterized by a model which allows for nonlinear behavior. In this paper, an attempt is made to examine the nonlinear behavior of returns of four exchange rates of Indian rupee with respect to Euro, British Pound, US Dollar and Japanese Yen, by utilizing tests based on nonlinear modeling. The application of BDS test strongly rejects the null hypothesis of independent and identical distribution of the return series as well as the ARMA residual series for all the exchange rates under study. This is consistent with nonlinear dependence in the return series. However, it is not enough to merely identify nonlinear dependence. So, the study investigates whether the nonlinear dependence is caused by predictable conditional volatility. It is found that GARCH(p, q) model fits all the market return series adequately and accounts for the nonlinearity found in the series. [ABSTRACT FROM AUTHOR]

Against the background of international scenario of exchange rate volatility, the present paper analyzes rupee volatility and its impact on the macroeconomic variables of India considering data for the period 1997-2013. The evidence shows that the exchange rate volatility of India is not purely a domestic phenomenon. Further, the results of log-log regression model show that the negative impact of depreciation is limited to inflation and trade balance. All other variables show positive impact. Thus, strong empirical evidence is obtained to conclude that the impact of appreciation on macroeconomic variables is higher as compared to that of depreciation on these variables. [ABSTRACT FROM AUTHOR]

The Reserve Bank of India (RBI) used exceptional monetary measures to address the taper tantrum-induced exchange market pressure on the rupee in the third quarter of 2013. This paper provides theoretical and empirical justifications for using the monetary policy to defend the exchange rate under exceptional circumstances, and also outlines certain preconditions which may determine the success of such a policy response. The empirical hypothesis on the effectiveness of an interest rate defence has been examined using four alternative approaches: first, the conventional monetary approach to exchange rate; second, uncovered interest rate parity (UIP) condition in the presence of timevarying risk premium; third, impact assessment in a vector auto regression (VAR) framework; and fourth, a comparative quantitative assessment of the costs associated with depreciation of the rupee relative to a higher interest rate for the Indian corporate sector in a panel regression framework. The scope for different policy inferences that could be derived from the results of alternative approaches highlight the need for a careful assessment of preconditions while designing and applying monetary measures to stabilise the exchange rate. [ABSTRACT FROM AUTHOR]

The paper analyzes the relation between the movement of Indian rupee and movement of BSE IT sector index over the five-year calendar period (2009-2013) by taking monthly closing returns over the study period. The BSE IT Index is a sector-specific index of BSE and includes leading IT companies from India. The tools used for the purpose of studying this relation include Granger Causality (F Wald) restricted-unrestricted approach test which has been done bilaterally, Dickey-Fuller tests for stationarity of variables, Engle Granger Cointegration and Vector Error Correction Model to establish the long-term relation between the variables and variance decomposition of the error term. The model uses an autoregressive regression and has a number of lags and therefore optimal lag length has been determined using AIC and SIC criteria. The results of the study clearly show that BSE IT Index is causing movement in rupee, however, this is only from 4th lag onwards. On the other hand, the results could not establish a reverse relation or rupee causing movement in BSE IT Index for the period of study. The AIC and SIC results for model testing showed that the 4 lag model was the most appropriate model under study out of the 8 lags that were considered. The coefficient of the error term in ECM regression was negative, showing stable long-run equilibrium. Moreover, the result also showed that adjustment mechanism was backwards. [ABSTRACT FROM AUTHOR]

Purpose -- The purpose of this paper is to examine the presence of the turn-of-month effect in the Indian currency market for selected currency pairs: USD-INR, EUR-INR, GBP-INR and JPY-INR, from January 1999 to April 2014. Design/methodology/approach -- Ordinary least square regression analysis is used to examine the presence of the turn-of-month effect and to test the efficiency of the Indian currency market. The characteristics of the returns during the turn-of-month days are compared with that of the non-turn-of-month trading days. The sample period is later divided into two sub-periods, that is, pre- and post-2008 to capture the behavior of returns before and after the 2008 financial crisis. Findings -- The results indicate the existence of pricing patterns which are unique to individual currencies. For the entire sample period, USD and JPY exhibit turn-of-month effect and the returns in turn-of-month trading days are significantly lower than the returns during non-turn-of-month trading days. For the sub-period before 2008, all the currencies exhibit significant turn-of-month effects and the returns in the turn-of-month trading days are significantly lower than those in the non-turn-of-month trading days. However, post-2008; this effect vanishes for all the currencies except for USD. Practical implications -- The results have important implications for both traders and investors. The findings suggest that the investors might not be able to earn excess profits by timing their positions in some particular currencies taking the advantage of turn-of-month effect which in turn indicates that the currency markets have become more efficient with time. The results are in conformity with those reported for the developed markets. Originality/value -- To the best of the author's knowledge, no study has yet examined these calendar anomalies in the currency markets using data which covers two important periods, pre-2008 and post-2008. Therefore, we provide a pioneer study in which we analyze the calendar anomalies in an emerging currency market (India) by segregating the data before and after 2008 financial crisis. [ABSTRACT FROM AUTHOR]

Indian rupee has been depreciating since May 2013 creating many dimensional trends and issues to be looked at or to be examined. If a currency is depreciating it implies that the value has gone down in relation to another currency. Presently, the value of rupee has declined from nearly Rs. 55 to a dollar to nearly 69 rupees a dollar. This is because portfolio investors are now taking back their money from emerging markets causing demand for dollars (international currency for payments) to increase hence, pulling down Indian currency. The present paper analyzing the deprecating trends since independence in the context of Indian economy and also discusses issues which have come up due to depreciation of Indian rupee. [ABSTRACT FROM AUTHOR]

THE price of one currency in terms of another currency (exchange rate) is a very important variable for an open economy in the global market, because it affects the overall economic performance and growth of the economy. So, the relationship between exchange rate and the related macro-economic factors causing variability in the value of the former carries a high degree of significance for any open economy. The present paper aims to identify those macro-economic factors that affect the price of Indian currency (Rupee) and their inter-relationship with the latter. Also, the study includes the fluctuations of Indian currency against the Dollar (INR/USD) post globalization and suggests measures to control the devaluation of the Indian rupee. Purpose: To analyze the effect of select macro-economic factors influencing the IndianRupee value against US Dollar post- globalization. Design/Methodology/Approach: The nature of research is Exploratory & Analytical that generates a posteriori hypothesis by analyzing a data-set and looking for potential relations between variables. Findings: Exchange rate is highly dependent on the five select independent variables taken up for this study. Research Implications: A strong relation between the dependent & independent variables suggests that steps taken to compress imports and promote FDI in explored & unexplored sectors can help improve the current rupee value. [ABSTRACT FROM AUTHOR]

This study is an attempt to estimate the dynamics (volatility) of Indian rupee instability against four major world currencies, i.e., US dollar, pound sterling, euro and Japanese yen, using 3,340 daily observations over a period of 13 years from January 3, 2000 to September 30, 2013. This paper uses the Generalized Autoregressive Conditional Heteroskedastic (GARCH) models to estimate volatility (conditional variance) in the daily log rupee value. The models include both symmetric and asymmetric that capture the most common stylized facts about rupee exchange returns such as volatility clustering and leverage effect. It is evident from the findings that asymmetric models are superior to symmetric models in providing a better fit for the exchange rate volatility because of leverage effect. [ABSTRACT FROM AUTHOR]

Emphasizing the need for risk mitigation arising out of excess volatility in rupee experienced by India post implementation of the market determined exchange rate regime in 1993, currency futures were introduced in India in 2008, and currency trading has become one of the most important financial operations since then. In this paper, an attempt has been made to measure and compare the market risk prediction ability of historical simulation, Monte-Carlo simulation, Exponentially Weighted Moving Average (EWMA) and linear parametric VaR approaches for Indian currency spot and futures market. Using the data from 2008 to 2013, the VaR associated with the three main currencies in the economy, namely, US dollar, euro and UK pound sterling, is calculated. Conditional and unconditional coverage tests have been applied to backtest the results of various VaR approaches. The results indicate that Monte-Carlo simulation is appropriate in predicting market risk. Further, it is also found that risk seems to be higher in the future market as compared to the underlying markets. [ABSTRACT FROM AUTHOR]

Abstract: This paper outlines a methodology to identify informal settlements out of high resolution satellite imagery using the concept of lacunarity. Principal component analysis and line detection algorithms were applied alternatively to obtain a high resolution binary representation of the city of Hyderabad, India and used to calculate lacunarity values over a 60 × 60 m grid. A number of ground truthing areas were used to classify the resulting datasets and to identify lacunarity ranges which are typical for settlement types that combine high density housing and small dwelling size – features characteristic for urban slums in India. It was discovered that the line detection algorithm is advantageous over principal component analysis in providing suitable binary datasets for lacunarity analysis as it is less sensitive to spectral variability within mosaicked imagery. The resulting slum location map constitutes an efficient tool in identifying particularly overcrowded areas of the city and can be used as a reliable source in vulnerability and resilience assessments at a later stage. The proposed methodology allows for rapid analysis and comparison of multi-temporal data and can be applied on many developing urban agglomerations around the world. [Copyright &y& Elsevier]

In this paper we assess the equilibrium value of the Mauritian rupee in 2006-7 and over the medium run using two structural models. First, we derive a current account-based measure of the exchange rate equilibrium using the macroeconomic balance approach. Second, we estimate a reduced-form fundamental equilibrium exchange rate measure. Our results, which are robust to an alternative non-econometric approach, suggest that the Mauritian rupee was aligned with its equilibrium value in 2006-7 and little adjustment appeared necessary over the medium run. [ABSTRACT FROM AUTHOR]

Financial or economic crisis of 2008 and its severe negative impact on the human race is currently one of the focal themes of financial research. During this crisis period the Indian Rupee (INR) has significantly lost its ground compared to the United States Dollar (USD). In the present paper, we address the issues identifying warning and action points in a time sequential monitoring of the exchange rate records. We developed some approximate power 1 partially sequential nonparametric tests that are based on both usual and sequential ranks. Proposed procedures necessarily help us to capitalize the best features of the two different rank procedures. We use Wilcoxon score and the idea of curved stopping boundaries as in Bandyopadhyay et al. (2008). We vividly present our numerical findings obtained by sequential Monte-Carlo procedures. We aim at controlling the type I error rate in course of structural monitoring. [ABSTRACT FROM AUTHOR]

In recent years forecasting of financial data such as interest rate, exchange rate, stock market and bankruptcy has been observed to be a potential field of research due to its importance in financial and managerial decision making. Survey of existing literature reveals that there is a need to develop efficient forecasting models involving less computational load and fast forecasting capability. The present paper aims to fulfill this objective by developing two novel ANN models involving nonlinear inputs and simple ANN structure with one or two neurons. These are: functional link artificial neural network (FLANN) and cascaded functional link artificial neural network (CFLANN). These have been employed to predict currency exchange rate between US$ to British Pound, Indian Rupees and Japanese Yen. The performance of the proposed models have been evaluated through simulation and have been compared with those obtained from standard LMS based forecasting model. It is observed that the CFLANN model performs the best followed by the FLANN and the LMS models. [Copyright &y& Elsevier]

This paper investigates the effects of the East Asian crisis on the Indian economy and exchange rate movements. Despite the contagion effects that profoundly affected the other crisis-hit countries, the Indian economy and the rupee were found less affected. Reforms after the 1990–1991 crisis, control of capital flows, weak economic linkages with crisis-affected countries and stabilization policies that include intervention in the foreign exchange market and tightening of monetary policy are reasons for the insulation of the Indian economy from the crisis. [ABSTRACT FROM AUTHOR]

This paper examines the spatial implications of India's new economic policy operating through two instrumentalities of stabilisation and structural adjustment. Stabilisation is aimed at correcting the balance of payments situation and reducing the deficit in the Union government budget, which has had an adverse effect on social development, employment generation, and poverty alleviation in hill, tribal, drought prone and other backward areas. Devaluation of the rupee benefitted the major foreign remittance receiving states like Kerala, Gujarat, Punjab and Tamil Nadu. Structural adjustment, through rationalisation of trade, industrial, agricultural, human resource development, and power policies had spatial implications of varying nature. Trade policy enhanced investment attraction of big urban industrial centres; industrial policy attracted foreign direct investment in mineral-rich backward states; and export orientation in agriculture was to a greater advantage of rice and cotton producing states. Reduction in subsidies for fertilisers had more serious implications for the agriculturally backward states. Higher tariffs in the power sector were to the disadvantage of Punjab, Haryana, Tamil Nadu and Kerala. Urban-rural and inter-state disparities in social development widened, with relatively lower allocations to education and health. On balance, though new economic policy offers new opportunities it does have a spatially differential impact. [ABSTRACT FROM AUTHOR]

In his address to nation on 8th November, 2016, prime minister of India Sh. Narendera Modi suddenly announced the demonetization of high denomination currency notes of Rs500 and Rs 1000. Whole economy got panicked on this sudden move of the government. All the economy felt immediate effects. Some sectors of economy started growing at very fast rate whereas some suffered a considerable loss. This research paper tried to analyze the effects of demonetization on the key sectors of the economy. It was found the digital payment companies, banks etc. got benefitted from demonetization, whereas some sectors such as reality, MSME got a considerable downfall. [ABSTRACT FROM AUTHOR]

Our objective is to estimate the capital required to launch, scale and sustain the operation of health microinsurance plans. We develop algorithms to estimate operating costs, capital or loan requirements, interest earned, repayments, and scaling projections. We check the plausibility of assumptions using the data of two CBHI plans. A prototype plan covering 40,000 persons in India requires USD 62,477 to offset deficits in the initial years if its long-term operating costs are not to exceed 20% of the premium and the claims ratio is to stabilise at around 70%. Capital requirements drop significantly when confidence levels are lower than 99.9. Fifteen years are required (after a five-year moratorium) to repay the loan in full plus interest at 5% p.a. in USD (10.96% in Indian rupees). It is possible to attain sustainability of health microinsurance schemes by providing the necessary initial capital as a loan and being very attentive to five parameters: enrolments, premiums, operating costs, renewal rates, and claims ratio. [ABSTRACT FROM AUTHOR]