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Gary D. Thompson Almuhanad Melhim The University of Arizona Gary D. Thompson Almuhanad Melhim The University of Arizona Estimating Import Demand for Fresh.

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Presentation on theme: "Gary D. Thompson Almuhanad Melhim The University of Arizona Gary D. Thompson Almuhanad Melhim The University of Arizona Estimating Import Demand for Fresh."— Presentation transcript:

1 Gary D. Thompson Almuhanad Melhim The University of Arizona Gary D. Thompson Almuhanad Melhim The University of Arizona Estimating Import Demand for Fresh Citrus Linda Calvin Economic Research Service Linda Calvin Economic Research Service

2 Why Study Import Demand? Quantify Impacts of SPS Measures:  Elasticities (Own- & Cross-Price)  Flexibility Estimates  Estimate Welfare of Impacts SPS Quantify Impacts of SPS Measures:  Elasticities (Own- & Cross-Price)  Flexibility Estimates  Estimate Welfare of Impacts SPS

3 Characteristics of SPS Measures Clementines from Spain  Country- & Even Region-Specific  Date-Specific  Aggregated Data Not Appropriate  Aggregated Data Not Appropriate Clementines from Spain  Country- & Even Region-Specific  Date-Specific  Aggregated Data Not Appropriate  Aggregated Data Not Appropriate

4 SpainSpain S. Africa AustraliaAustralia MoroccoMorocco U.S. Mandarin Imports, 2000-03 Source: FATUS

5 Supply Side Drives Availability Clementines from Spain  Zero Import Quantity  No Import Price Unobservable, Not Unobserved  Not Censoring; Partial Truncation: Missing Price & Quantity  Micro-Data Censoring Models Not Appropriate Clementines from Spain  Zero Import Quantity  No Import Price Unobservable, Not Unobserved  Not Censoring; Partial Truncation: Missing Price & Quantity  Micro-Data Censoring Models Not Appropriate

6 Possible Approaches to Truncation  Incidental Truncation Sample selection is typically cross- sectional. Sample selection of import availability depends on agro-climatic factors (e.g. weather throughout the year)  Incidental Truncation Sample selection is typically cross- sectional. Sample selection of import availability depends on agro-climatic factors (e.g. weather throughout the year)

7 Truncation & Demand Systems  Multiple selectivity equations + Demand system equations Cross-Sectional - Sequential Selectivity Models (Lahiri & Song)  Multiple selectivity equations + Demand system equations Cross-Sectional - Sequential Selectivity Models (Lahiri & Song)

8 MandarinsMandarins OrangesOranges TangerinesTangerines Partial Truncation at Product Level

9 Selectivity Equations: Probit/Logit  Binary Regression: Dep. Vbl. = 0 if no imports = 1 if positive imports = 1 if positive imports Exp. Vbls.: Temperature; Precipitation in Production Region in Production Region  Binary Regression: Dep. Vbl. = 0 if no imports = 1 if positive imports = 1 if positive imports Exp. Vbls.: Temperature; Precipitation in Production Region in Production Region

10 Marshallian Demand Equations  Incomplete Demand System LINQUAD: Weak integrability guarantees reliable elasticity and welfare measures.  Incomplete Demand System LINQUAD: Weak integrability guarantees reliable elasticity and welfare measures.

11 Demand Equations + Truncation  Introduce Correction for Partial Truncation as Demographic Shifter in LINQUAD:  Not just inverse Mills ratio  Multivariate normal is maintained  Multivariate normal is maintained  Introduce Correction for Partial Truncation as Demographic Shifter in LINQUAD:  Not just inverse Mills ratio  Multivariate normal is maintained  Multivariate normal is maintained

12 Choice of Samples for Estimation 1. Consecutive Months Each Year  Oct. - Feb. Season; 1992-93 to 2002-03 2.Aggregate Temporally to Eliminate Zero Quantities & Missing Prices Quantities & Missing Prices  Semi-annual; 1989 - 2003 1. Consecutive Months Each Year  Oct. - Feb. Season; 1992-93 to 2002-03 2.Aggregate Temporally to Eliminate Zero Quantities & Missing Prices Quantities & Missing Prices  Semi-annual; 1989 - 2003

13 Uncompensated Elasticities, Sample Median TangerineMandarinOrange Tangerine -0.026-4.0160.463 Mandarin -0.006-4.3750.039 Orange0.374-0.670-2.268 Sample: Monthly, Oct.-Feb., 1992 – 2003 (T = 55) TangerineMandarinOrange Tangerine -0.026-4.0160.463 Mandarin -0.006-4.3750.039 Orange0.374-0.670-2.268 Sample: Monthly, Oct.-Feb., 1992 – 2003 (T = 55)

14 Uncompensated Elasticities, Sample Median TangerineMandarinOrange Tangerine -2.1930.543-0.134 Mandarin 0.020-0.326-0.463 Orange0.133-0.498-0.101 Sample: Semi-annual, 1989 – 2003 (T = 30) TangerineMandarinOrange Tangerine -2.1930.543-0.134 Mandarin 0.020-0.326-0.463 Orange0.133-0.498-0.101 Sample: Semi-annual, 1989 – 2003 (T = 30)

15 Oct99Oct99 Own-Price Elasticity, Mandarins Oct00Oct00 Oct01Oct01 Oct02Oct02 Suspension of Spanish Imports

16 Cross-Price Elasticity, Mand.-Orange Oct99Oct99 Oct00Oct00 Oct01Oct01Oct02Oct02 Suspension of Spanish Imports

17 Correction for Truncation 1.Necessary for modeling seasonal availability of imports (or exports). 2.Yields reasonable, if highly variable, elasticity estimates. 3.Uses data readily available, e.g. FATUS, NOAA. 1.Necessary for modeling seasonal availability of imports (or exports). 2.Yields reasonable, if highly variable, elasticity estimates. 3.Uses data readily available, e.g. FATUS, NOAA.

18 Future Work  Demand for Domestic & Imported Fresh Citrus  Apply to other specialty crops, e.g. asparagus, fresh tomatoes.  MLE or Non-Parametric Estimation  Demand for Domestic & Imported Fresh Citrus  Apply to other specialty crops, e.g. asparagus, fresh tomatoes.  MLE or Non-Parametric Estimation


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