YEI EconOlympiad Submission

Summary

The presentation evaluates whether policy changes around 2022—discussed as price ceilings—reduced prescription-drug inflation in the United States. The presenters distinguish between lowering the level of prices and slowing their rate of growth, arguing that inflation is the more relevant near-term measure of policy effects.

Economic background

A price ceiling is a legal maximum price. If set below the market price, it can make medicines more affordable in the short run.

In the standard supply-and-demand model, however, a lower permitted price can reduce the quantity firms are willing to supply while increasing the quantity consumers want. The resulting shortage could appear as delayed access or reduced investment in research and new drug development—not necessarily just empty shelves.

The presenters therefore frame price ceilings as a trade-off: immediate affordability gains may come with longer-run supply or innovation risks.

Method and findings

The analysis uses monthly U.S. prescription-drug price data from the Bureau of Labor Statistics, accessed through the Federal Reserve’s FRED database.

The presenters:

1. Converted price levels to inflation by log-transforming the price index and taking its first difference to estimate monthly price growth.
2. Inspected the data by plotting monthly inflation and using a 12-month moving average to make broader trends easier to see.
3. Tested inflation persistence with autocorrelation analysis and an AR(1) regression to assess whether current inflation is related to inflation in the previous month.
4. Compared periods using a Welch mean comparison to test whether average inflation differed before and after 2022.
5. Estimated a post-2022 shift with an AR(1) model that included a dummy variable equal to zero before 2022 and one afterward.

The main results were:

• Average inflation fell from 0.323% before 2022 to 0.203% afterward, but the Welch test’s p-value of 0.69 indicates that this difference was not statistically significant.
• Inflation showed persistence: the presentation reports lag-one autocorrelation of 0.457 and says the lagged inflation term in the AR(1) model was highly statistically significant.
• The post-2022 dummy was negative, consistent with lower inflation after 2022, but was not statistically strong enough to establish that policy caused the decline.
• A comparison of consumer-price inflation (CPI) and producer-price inflation (PPI) showed that the series did not move perfectly together. The presenters interpret this as evidence that consumer prices are influenced not only by production costs but also by factors such as market structure, insurance, negotiations, and public policy.

The overall conclusion is cautious: inflation declined after 2022, but the analysis does not establish that the policy changes caused the decline. Because drug-price inflation has momentum, the presenters argue that price ceilings alone are unlikely to change its trajectory quickly or permanently.

Policy recommendations

The presentation recommends a layered approach:

• Encourage generic and biosimilar competition by reducing regulatory and legal barriers to entry. The presenters argue that competition can increase supply, reduce market power, and lower prices over the longer run.
• Use negotiated pricing for selected drugs, focusing on high-cost medicines with weak competition and substantial pricing power.
• Provide targeted patient support through subsidies or limits on out-of-pocket spending. This could improve affordability for vulnerable patients without imposing broad price controls that might create shortages.
• Treat price ceilings as one possible tool, not a complete solution. The proposed package combines affordability protections with reforms intended to address market structure and bargaining power.

Speakers and sources

• Presenters: The subtitles do not distinguish individual speakers. The video metadata identifies the submission team as EconLP, with JR Lucas Pascoal and Joseph Rench.
• Data sources: U.S. Bureau of Labor Statistics prescription-drug CPI and pharmaceutical PPI data, accessed through the Federal Reserve’s FRED database.
• Research cited: Health-economics research on generic entry and drug prices, attributed in the subtitles to “Frank and Selke…,” with the second name unclear in the autogenerated captions.