The Impact of Population Policies
Comment
Bibliographic Data
| ID | 21056982 |
|---|---|
| Authors | James C Knowles (0000-0003-3917-3446), John S Akin, David K Guilkey |
| Year | 1994 |
| Volume | 20 |
| Issue | 3 |
| Pages | 611 |
| Publication date | 1994-09-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Population and Development Review (JOURNAL) |
| Journal identifiers | ISSN: 0098-7921 • E-ISSN: 1728-4457 |
| Publisher | JSTOR (PUBLISHER) |
| DOI | 10.2307/2137603 |
| OpenAlex | W2062055273 |
| Language | EN |
| Citations received | 14 |
Lant Pritchett has argued that on the basis of empirical findings variations in fertility desires account for most of the variation in fertility rates across countries and that access to contraception contributes at best a significant but numerically small (2-3%) independent effect. Pritchett concluded that changing fertility desires and increased contraceptive access cause some trivial fertility reductions. Pritchetts empirical analysis is believed to be seriously flawed by his use of an essentially tautological statistical model. The focus of this comment on Pritchett is on the inappropriateness of the statistical model itself. The first section presents cross-national regressions of the total fertility rate (TFR) on three alternative measures of fertility preferences: the average ideal number of children; Lightbournes and Westoffs desired total fertility rate (DTFR); and Bongaartss wanted total fertility rate. The dramatic result obtained namely that two measures of desired fertility explain about 90% of the variation in the total fertility rate is an artifact of the model stemming from the inclusion of a slight transformation of the dependent variable itself as the explanatory variable. Moreover the results obtained are equally consistent with those one would obtain if the measures of excess fertility used were simply random noise. If the correct model is in fact that described by equations it is not surprising that instrumental variable estimation raises estimates of beta toward a value of one; nor is it surprising that other explanatory variables (e.g. contraceptive prevalence family planning program effort unmet need) when added to a regression of TFR on DTFR tend to be insignificant. When a variable is essentially regressed on itself little variation remains to be explained by other factors
Economics · Political science · Population · Sociology · Demographic Trends and Gender Preferences · Demography · Global Maternal and Child Health · Insurance, Mortality, Demography, Risk Management
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Population and Fairness
Do Family Planning Programs Affect Fertility Preferences? A Literature Review
The Role of Contraceptive Supply and Demand in Mexican Fertility Decline
Family planning impact evaluation
Spatial differences in fertility decline in Kenya
Family planning program effects on contraceptive use in Morocco, 1992–1995
Explaining fertility transitions
Desired Fertility and Number of Children Born Across Time and Space
How the World Survived the Population Bomb
The Impact of the Family Planning Supply Environment on Contraceptive Intentions and Use in Morocco
The Impact of Family Planning Service Provision on Contraceptive‐use Dynamics in Morocco
Family Planning Program Effects
| Citations per year | 0.48 |
|---|---|
| Citation span | 1997 - 2016 (20) |
| Highly cited | No |