TY - JOUR A1 - Kozicka, Marta A1 - Weber, Regine A1 - Kalkuhl, Matthias T1 - Cash vs. in-kind transfers BT - the role of self-targeting in reforming the Indian food subsidy program JF - Food Security N2 - Historically, India has relied on subsidizing staple food as a major instrument in improving food security. Recently, however, cash transfers have entered the debate as an alternative, as they are associated with lower market distortions, leakages and fiscal costs. This study contributes to this debate by analyzing India’s Targeted Public Distribution System (TPDS). Our main objective was to explain the under-purchase, or low take-up, from the TPDS, which is typically attributed to ‘leakage’, i.e. the diversion of food grains from eligible consumers. We provide an alternative solution based on self-targeting; while poorer households increase their consumption from the TPDS, wealthier households restrain from consuming subsidized commodities. Using a large household dataset, we estimated that such a voluntary opt-out system, based on income, would save a minimum of 6.5% of grains released through the TPDS. Besides these demand-driven aspects, our analysis indicates that poor regions perform better at lowering the diversion of grains and that large targeting errors exist among female-led households. Finally, we find substantial regional price differences that would benefit the poor and rural population under a uniform cash-transfer system that does not correct for regional price levels. KW - Food security KW - Policies KW - India KW - Targeted public distribution system KW - Self-targeting KW - Cash transfers Y1 - 2019 U6 - https://doi.org/10.1007/s12571-019-00942-x SN - 1876-4517 SN - 1876-4525 VL - 11 IS - 4 SP - 915 EP - 927 PB - Springer CY - New York ER - TY - JOUR A1 - Maheswaran, Rathinasamy A1 - Agarwal, Ankit A1 - Sivakumar, Bellie A1 - Marwan, Norbert A1 - Kurths, Jürgen T1 - Wavelet analysis of precipitation extremes over India and teleconnections to climate indices JF - Stochastic Environmental Research and Risk Assessment N2 - Precipitation patterns and extremes are significantly influenced by various climatic factors and large-scale atmospheric circulation patterns. This study uses wavelet coherence analysis to detect significant interannual and interdecadal oscillations in monthly precipitation extremes across India and their teleconnections to three prominent climate indices, namely, Nino 3.4, Pacific Decadal Oscillation, and Indian Ocean Dipole (IOD). Further, partial wavelet coherence analysis is used to estimate the standalone relationship between the climate indices and precipitation after removing the effect of interdependency. The wavelet analysis of monthly precipitation extremes at 30 different locations across India reveals that (a) interannual (2-8 years) and interdecadal (8-32 years) oscillations are statistically significant, and (b) the oscillations vary in both time and space. The results from the partial wavelet coherence analysis reveal that Nino 3.4 and IOD are the significant drivers of Indian precipitation at interannual and interdecadal scales. Intriguingly, the study also confirms that the strength of influence of large-scale atmospheric circulation patterns on Indian precipitation extremes varies with spatial physiography of the region. KW - Extreme precipitation KW - Teleconnection patterns KW - Wavelets KW - Partial wavelet coherence KW - India Y1 - 2019 U6 - https://doi.org/10.1007/s00477-019-01738-3 SN - 1436-3240 SN - 1436-3259 VL - 33 IS - 11-12 SP - 2053 EP - 2069 PB - Springer CY - New York ER -