scholarly journals Dealing with Incomplete Household Panel Data in Inequality Research

2010 ◽  
Author(s):  
Joachim R. Frick ◽  
Markus Grabka ◽  
Olaf Groh-Samberg
Keyword(s):  
Panel Data ◽  
Household Panel Data

scholarly journals Ageism Kills Brands

2021 ◽  
pp. 183933492110173
Author(s):  
Zachary William Anesbury ◽  
Steven Bellman ◽  
Carl Driesener ◽  
Bill Page ◽  
Byron Sharp
Keyword(s):  
Panel Data ◽  
Market Share ◽  
Household Panel Data ◽  
The Relationship ◽  
Physical Availability

Market share growth requires building mental and physical availability among all category buyers. However, if younger category buyers are more likely to purchase new-to-market products, then perhaps younger buyers are, relatively speaking, more important for growth. This research investigates the relationship between category buyer age, brand buyer age, and brand failure. When sub-brand buyer age is younger than category buyer age, the sub-brand is likely to be (a) new-to-market or (b) growing in market share. Older-than-category sub-brand-buyer age is likely for sub-brands that are (a) declining or (b) dead. Results from 17 years (1998–2014) of U.K. household panel data, including 5,913 sub-brands from 101 categories, show that age skews were uncommon (only 18% of sub-brands), and second, that growing, stable and declining sub-brands appealed equally to all ages. Finally, we identified that new launches and dead brands tend to skew to younger consumers, suggesting that new launches need to appeal to all ages to avoid failure.

Price elasticities of residential electricity demand: Estimates from household panel data in Bangladesh

2020 ◽  
Vol 92 ◽  
pp. 104937
Author(s):  
Hemawathy Balarama ◽  
Asad Islam ◽  
Jun Sung Kim ◽  
Liang Choon Wang
Keyword(s):  
Panel Data ◽  
Electricity Demand ◽  
Price Elasticities ◽  
Residential Electricity ◽  
Household Panel Data

scholarly journals Rainfall Forecasts, Weather, and Wages over the Agricultural Production Cycle

2014 ◽  
Vol 104 (5) ◽  
pp. 278-283 ◽  
Author(s):  
Mark R. Rosenzweig ◽  
Christopher Udry
Keyword(s):  
Panel Data ◽  
Agricultural Production ◽  
Negative Impact ◽  
District Level ◽  
Production Cycle ◽  
Early Season ◽  
Adverse Weather ◽  
Ex Ante ◽  
Agricultural Wages ◽  
Household Panel Data

We look at the effects of rainfall forecasts and realized rainfall on equilibrium agricultural wages over the course of the agricultural production cycle. We show theoretically that a forecast of good weather can lower wages in the planting stage, by lowering ex ante out-migration, and can exacerbate the negative impact of adverse weather on harvest-stage wages. Using Indian household panel data describing early-season migration and district-level planting- and harvest-stage wages over the period 2005-2010, we find results consistent with the model, indicating that rainfall forecasts improve labor allocations on average but exacerbate wage volatility because they are imperfect.

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