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Using the bottom-up approach of Romer and Romer (2010), we construct a narrative dataset of net-revenue shocks for Germany by extending the tax shock series of Hayo and Uhl (2014) and coding a shock series for social security contributions, benefits and transfers. We estimate the multiplier effects of shocks to net revenues, taxes, social security contributions, benefits and transfers in a proxy SVAR framework [Mertens and Ravn (2013)] and compare them with the top-down identification [Blanchard and Perotti (2002)]. We find multiplier effects of net-revenue components between 0 and 1 for both approaches. These estimates are comparably low and we investigate the differences.

Top-Down vs. Bottom-Up? Reconciling the Effects of Tax and Transfer Shocks on Output