How Linear Models Can Mask Non-Linear Causal Relationships. An Application to Family Size and Children's Education
AbstractMany empirical studies specify outcomes as a linear function of endogenous regressors when conducting instrumental variable (IV) estimation. We show that commonly used tests for treatment effects, selection bias, and treatment effect heterogeneity are biased if the true relationship is non-linear. In particular, using linear models can only lead to under-rejection of the null hypothesis of no treatment effects. In light of these results, we re-examine the recent evidence suggesting that family size has no causal effect on children's education. Following common practice, a linear IV estimator has been used, assuming constant marginal effects of additional children across family sizes. We show that the conclusion of no causal effect of family size is an artifact of the specification of a linear model, which masks significant marginal family size effects. Estimating a model that is non-parametric in family size, we find that family size matters substantially for children's educational attainment, but in a non-monotonic way. Our findings illustrate that IV estimation of models which relax linearity restrictions is an important addition to empirical research, particularly when OLS estimation and theory suggests the possibility of non-linear causal effects.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Research Department of Statistics Norway in its series Discussion Papers with number 586.
Date of creation: May 2009
Date of revision:
Instrumental variables; variable treatment intensity; treatment effect heterogeneity; selection bias; quantity-quality; family size; child outcome;
Other versions of this item:
- Mogstad, Magne & Wiswall, Matthew, 2009. "How Much Should We Trust Linear Instrumental Variables Estimators? An Application to Family Size and Children's Education," IZA Discussion Papers 4562, Institute for the Study of Labor (IZA).
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-06-03 (All new papers)
- NEP-ECM-2009-06-03 (Econometrics)
- NEP-EDU-2009-06-03 (Education)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Román David Zárate, 2013. "Family size and children quality: New evidence and new exogenous shocks in the case of Colombian Households," DOCUMENTOS CEDE 010588, UNIVERSIDAD DE LOS ANDES-CEDE.
- Aaberge, Rolf & Mogstad, Magne & Peragine, Vito, 2010.
"Measuring Long-Term Inequality of Opportunity,"
IZA Discussion Papers
4714, Institute for the Study of Labor (IZA).
- Aaberge, Rolf & Mogstad, Magne & Peragine, Vito, 2011. "Measuring long-term inequality of opportunity," Journal of Public Economics, Elsevier, vol. 95(3), pages 193-204.
- Aaberge, Rolf & Mogstad, Magne & Peragine, Vito, 2011. "Measuring long-term inequality of opportunity," Journal of Public Economics, Elsevier, vol. 95(3-4), pages 193-204, April.
- Rolf Aaberge & Magne Mogstad & Vito Peragine, 2010. "Measuring long-term inequality of opportunity," Discussion Papers 620, Research Department of Statistics Norway.
- Rolf Aaberge & Magne Mogstad & Vito Peragine, 2010. "Measuring long-term inequality of opportunity," Working Papers 158, ECINEQ, Society for the Study of Economic Inequality.
- Mogstad, M. & Wiswall, M., 2012.
"Instrumental variables estimation with partially missing instruments,"
Elsevier, vol. 114(2), pages 186-189.
- Mogstad, Magne & Wiswall, Matthew, 2010. "Instrumental Variables Estimation with Partially Missing Instruments," IZA Discussion Papers 4689, Institute for the Study of Labor (IZA).
- Parfait Eloundou-Enyegue & Sarah Giroux, 2012. "Fertility Transitions and Schooling: From Micro- to Macro-Level Associations," Demography, Springer, vol. 49(4), pages 1407-1432, November.
- Loken, Katrine Vellesen & Mogstad, Magne & Wiswall, Matthew, 2010.
"What Linear Estimators Miss: Re-Examining the Effects of Family Income on Child Outcomes,"
IZA Discussion Papers
4971, Institute for the Study of Labor (IZA).
- Løken, Katrine Vellesen & Mogstad, Magne & Wiswall, Matthew, 2011. "What Linear Estimators Miss: The E ects of Family Income on Child Outcomes," Working Papers in Economics 02/11, University of Bergen, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (J Bruusgaard).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.