In the present paper, Autoregressive Integrated Moving Average (ARIMA) models developed to forecast the prices of potato using time series data of eighteen years from 2002-2019. The best models selected by comparing Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), Mean Absolute Percent Error (MAPE), and Root Mean Square Error (RMSE). The study revealed that ARIMA (1,1,2), ARIMA (2,1,1)(0,0,2)[12], ARIMA (2,1,2), ARIMA (1,1,4)(0,0,1)[12], ARIMA (1,1,1)(0,1,2)[12], ARIMA (0,1,0)(0,1,1)[12], and ARIMA (3,1,3) were the best fitted models for forecasting of price of potato for the states of Utter Pradesh, West Bengal, Madhya Pradesh, Gujarat, Punjab, Tripura and India respectively. The prices of potato in Utter Pradesh, West Bengal and India will be increasing with the first-quarter providing the highest price. The prices of potato in Madhya Pradesh and Tripura will be highest in the fourth quarter. In Punjab, the prices of potato will be increasing with the third-quarter. The forecast shows that market prices of potato in Utter Pradesh, West Bengal, Madhya Pradesh, Gujarat, Punjab, Tripura, and overall India would be ruling in the highest value of .1208 `/qt, 1812 `/qt, 1345 `/qt, 1712 `/qt, 1354 `/qt, 2636 `/qt, and 1715 `/qt respectively for the year 2020.

The study attempts to examine the causal relation among export growth, inflation, foreign direct investment and real GDP growth rate for the period 1990-91 to 2018-19 using Vector Auto Regressive (VAR) model and Granger Causality test. Both the statistical techniques employed show similar results pertaining to the causal relationship among the variables selected for the study. The results show that FDI andamp; Real GDP growth have positive effect on export growth and there is no evidence of inflation alone causing export growth, but inflation along with FDI and Real GDP cause the Export growth. There is also evidence that export growth, inflation, real GDP growth together cause FDI. The results also indicate that none of the aforementioned economic variables either individually or jointly cause real GDP growth. The authors opine that slow growth in exports had been compensated by domestic demand and services-led growth in the process of economic growth during the period of study. The study stressed the need for introducing structural reforms to enhance the competitiveness of Indian products in the international markets. The focus should be on designing a new strategy for technology-driven export-oriented sectors as the export stability is positively associated with economic growth.

The study was carried out in Barmer district of Rajasthan to analyze economics of Isabgol production and constraints faced by farmers. The primary data were collected from total sample of 80 farmerandrsquo;s respondents. The study reveals that total cost of cultivation was higher ` 38407.69 per hectare on large farm, followed by ` 34132.15 on medium and ` 31281.96 on small farm and ` 34607.27 per hectare on overall farm. The cost of cultivation increases as farm size increase. It is observed from the result of F test p value is .001 which shows that there is statistically significant difference in cost of cultivation of Isabgol on different farm size category. The different cost on the basis of cost concept (Cost A1, A2, B1, B2, C1, C2 and C3) of Isabgol cultivation per hectare was calculated. The cost of production was found lower on large farm it was found to be ` 5053.64 per quintal followed by ` 5094.35 per quintal on medium farm, ` 5128.19 per quintal for small size farm which was found highest and ` 5092.06 per quintal for overall farm size. Farm business income, family labor income and farm investment income of Isabgol cultivation was found highest on large farm. The benefit cost ratio was found at 1.63 for overall farm size and was found to be 1.68 for large farm, 1.64 for medium farm and 1.63 for small farm. Crop damage by pest and diseases are the most important constraints faced by farmers in Isabgol production.