000			03148cam a22003617 4500
001			w14860
003			NBER
005			20211020111531.0
006			m o d
007			cr cnu||||||||
008			210910s2009 mau fo 000 0 eng d
100	1		_aGraham, Bryan S.
245	1	0	_aComplementarity and Aggregate Implications of Assortative Matching: _bA Nonparametric Analysis / _cBryan S. Graham, Guido W. Imbens, Geert Ridder.
260			_aCambridge, Mass. _bNational Bureau of Economic Research _c2009.
300			_a1 online resource: _billustrations (black and white);
490	1		_aNBER working paper series _vno. w14860
500			_aApril 2009.
520	3		_aThis paper presents methods for evaluating the effects of reallocating an indivisible input across production units, taking into account resource constraints by keeping the marginal distribution of the input fixed. When the production technology is nonseparable, such reallocations, although leaving the marginal distribution of the reallocated input unchanged by construction, may nonetheless alter average output. Examples include reallocations of teachers across classrooms composed of students of varying mean ability. We focus on the effects of reallocating one input, while holding the assignment of another, potentially complementary, input fixed. We introduce a class of such reallocations -- correlated matching rules -- that includes the status quo allocation, a random allocation, and both the perfect positive and negative assortative matching allocations as special cases. We also characterize the effects of local (relative to the status quo) reallocations. For estimation we use a two-step approach. In the first step we nonparametrically estimate the production function. In the second step we average the estimated production function over the distribution of inputs induced by the new assignment rule. These methods build upon the partial mean literature, but require extensions involving boundary issues. We derive the large sample properties of our proposed estimators and assess their small sample properties via a limited set of Monte Carlo experiments.
530			_aHardcopy version available to institutional subscribers
538			_aSystem requirements: Adobe [Acrobat] Reader required for PDF files.
538			_aMode of access: World Wide Web.
588	0		_aPrint version record
690		7	_aC14 - Semiparametric and Nonparametric Methods: General _2Journal of Economic Literature class.
690		7	_aC21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions _2Journal of Economic Literature class.
690		7	_aC52 - Model Evaluation, Validation, and Selection _2Journal of Economic Literature class.
700	1		_aImbens, Guido W. _913314
700	1		_aRidder, Geert. _919403
710	2		_aNational Bureau of Economic Research.
830		0	_aWorking Paper Series (National Bureau of Economic Research) _vno. w14860.
856	4	0	_uhttps://www.nber.org/papers/w14860
856			_yAcceso en línea al DOI _uhttp://dx.doi.org/10.3386/w14860
942			_2ddc _cW-PAPER
999			_c333262 _d291824