Theoretical Inflation for Unavailable Products by Rachel - - PowerPoint PPT Presentation

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Theoretical Inflation for Unavailable Products by Rachel - - PowerPoint PPT Presentation

Oct 07, 2023 96 likes •360 views

Theoretical Inflation for Unavailable Products by Rachel Soloveichik ESCoE Virtual Conference, September 16 th to 18 th Disclaimer: The views in this presentation reflect those of the author and not necessarily those of the Department of

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Theoretical Inflation for Unavailable Products

by Rachel Soloveichik ESCoE Virtual Conference, September 16th to 18th

Disclaimer: The views in this presentation reflect those of the author and not necessarily those of the Department of Commerce or the Bureau of Economic Analysis.

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Preview of Theoretical Strategy

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  • Hotel prices are higher in dense urban regions

– Despite the higher prices, tourists still flock to cities with desirable amenities that aren’t available in rural regions

  • This observed behavior can be used to estimate

theoretical inflation rates for unavailable products

Louisiana Vacations: New Orleans vs. Rural Region

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Preview of Empirical Results

  • Time spent at retail and recreational locations

is a proxy for product availability

– Product availability started dropping in March, bottomed

  • ut in April and slowly recovered in May and June
  • Theoretical inflation was at least 1.2

percentage points above the CPI in Q1 and 4.9 percentage points in Q2

– Published economic statistics miss approximately one third

  • f the theoretical drop in real consumption
  • Two data appendixes provide with detailed

data on specific products and specific regions

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Outline of Presentation

  • Review of price measurement literature
  • Development of new model to estimate

theoretical prices for unavailable products

  • Empirical data on the exact unavailable

products

– Unavailable products include both products restricted under a government stay-in-place order and products that consumers voluntarily avoid

  • Regional estimates of product unavailability in

the first and second quarter of 2020

– This unavailability is then used to calculate regional inflation rates

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Theoretical Price Measurement Problem

  • Laspeyres price index formula:

– Price IndexT = w10(p1T/p10)+ w20(p2T/p20)+…+ wn0(pnT/pn0) – This formula requires prices for every product

  • The CPI assumes that unavailable products

without price data have similar inflation as comparable products with price data

– This assumption appears to be accurate in normal economic times (Bradley 2003) – However, the assumption might not apply when stay-in-place policies suddenly make broad product categories unavailable

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Relevant Price Index Literature

  • “New goods”:

– (Hausman 1999), (Hausman 1997), (Petrin 2002), (Goolsbee and Petrin 2004), (Berndt et al. 1996), (Nordhaus 1996), (Diewert and Feenstra 2019), and (Diewert et al. 2019)

  • “Outlet substitution bias”:

– (Reinsdorf 1993), (Hausman and Liebtag 2009), and (Greenlees and Mclelland 2008)

  • “Variety bias”:

– (Feenstra 1994), (Broda and Weinstein 2010), and (Handbury and Weinstein 2014)

  • None of these literatures match COVID-19

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New Price Measurement Model

  • Tourists choose a rural or urban vacation

– Six products: Housing, goods 1&2, services 1&2, and amenity

– The amenity is only available in urban regions

  • Assumption: rational tourists visit the region

where a vacation budget buys the most utility

– Weather and travel costs are similar in the two regions – Theoretical rural prices equal theoretical urban prices, so that – The price premium for the unavailable rural amenity is ipaR = [(1–whphR - (wg1pg1R+wg2pg2R)- (ws1ps1R+ws2ps2R)]/wa

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Theoretical Prices for Unavailable Products

  • Assumption: the price premium for unavailable

tourist amenities is smaller than the price premium for nonessential goods and services

– Tourist amenities are generally considered more discretionary than nonessential products like clothing or elective surgery – Tourists are better able to plan around unavailable products

  • Comparing price indexes:

Theoretical Prices ≥whphSIP +wg1pg1SIP+ ws1ps1SIP +(wg2+ ws2 + wa)ipaR Quasi-BLS Prices =[whphSIP +(wg1+ wg2) pg1SIP + (ws1+ ws2)pg1SIP]/(1-wa)

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Data Used to Measure Theoretical Inflation

  • ipaR are calculated using these data sources:

– BEA’s regional income account gives phR, (wg1pg1R+wg2pg2R)/(wg1+wg2), and (ws1ps1R+ws2ps2R)/(ws1+ws2) – BEA’s travel and tourism account gives wh, wg1+wg2, ws1+ws2, and wa – The paper calculates ipaR = 1.59 in the average region

  • Theoretical prices are calculated using this data:

– BLS reports low monthly inflation for phSIP, pg1SIP, and pg1SIP – Appendix A reports product unavailability in a full stay-in-place policy: wh=0.20, wg1=0.27 wg2=0.05, ws1=0.31, ws2=0.17, wa=0.02 – Appendix B reports actual product unavailability for every region

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Theoretical Inflation in Q1 and Q2 of 2020

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Data on Actual Product Unavailability

  • Google’s Mobility Trends gives mobility changes

– Most unavailable products are sold at retail and recreational locations, so this paper focuses on that category – Dataset is publicly available at the day/county level

  • American Time Use Survey (ATUS) gives normal

mobility levels

– The paper calculates mobility levels for each region and day type – Mobility for smaller regions is smoothed to reduce volatility

  • Weather Underground gives daily weather

– Holding local policy fixed, mobility is higher in pleasant weather

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ATUS Mobility for 2003-2018

Minutes Per Day at Retail and Recreational Locations

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Average Mobility for March 2020

Minutes Per Day at Retail and Recreational Locations

9/9/2020 14

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Average Mobility for April 2020

Minutes Per Day at Retail and Recreational Locations

9/9/2020 15

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Average Mobility for May 2020

Minutes Per Day at Retail and Recreational Locations

9/9/2020 16

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Average Mobility for June 2020

Minutes Per Day at Retail and Recreational Locations

9/9/2020 17

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Impact of Temperature on Mobility

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Impact of Humidity on Mobility

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March Adjustment for Weather and Day

Minutes Per Day at Retail and Recreational Locations

9/9/2020 20

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April Adjustment for Weather and Day

Minutes Per Day at Retail and Recreational Locations

9/9/2020 21

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May Adjustment for Weather and Day

Minutes Per Day at Retail and Recreational Locations

9/9/2020 22

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June Adjustment for Weather and Day

Minutes Per Day at Retail and Recreational Locations

9/9/2020 23

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Summary of Actual Mobility Changes

  • ATUS respondents normally spend 75 minutes

per day at retail and recreational locations

– About 75 percent of this time is spent on nonessential activities

  • Almost every region sees a mobility drop in 2020

– Adjusted time fell 13 minutes per day in March, 33 minutes per day in April, 23 minutes per day in May, and 15 minutes per day in June

– Theoretical inflation was at least 1.2 percentage points above the CPI in Q1 and 4.9 percentage points above the CPI in Q2

  • Wealthy urban regions saw larger mobility drops

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Theoretical Inflation vs. Income in 2018 Bubble size is proportional to regional population

9/9/2020

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Conclusion

  • Inflation is underestimated when many

common goods and services are unavailable

– The paper then develops a new model to estimate theoretical cost-of-living when products are unavailable

  • The paper collected detailed data on both

potential and actual product unavailability

– Theoretical inflation was at least 1.2 percentage points above the CPI in Q1 and 4.9 percentage points above the CPI in Q2 – The published economic statistics miss approximately one third of the theoretical drop in real consumption

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