Wednesday, May 13, 2026

Adam Smith and the Role of the Towns in Feudal Europe

By Mark Koyama.

Abstract 

"Adam Smith’s account of medieval towns in Book III of The Wealth of Nations remains one of the most influential analyses of how commerce transformed feudal Europe. This pa- per formalizes Smith’s argument as a game between kings, lords, and towns. The king-town alliance emphasized by Adam Smith emerges when towns are wealthy enough to offer fiscal and military support but lords remain a serious threat. However, when kings become exces- sively predatory, towns may ally with lords (as in the Magna Carta crisis); when towns are too weak to offer substantial support, kings ally with lords instead (as in Eastern Europe). A dynamic extension shows that the king-town equilibrium is self-undermining: commercial growth erodes lordly military power through Smith’s “diamond buckles” mechanism, even- tually enabling royal absolutism. In contrast, the king-lords equilibrium is self-reinforcing, suppressing urban development and preserving feudal institutions. The framework highlights how small differences in initial urban development could generate dramatically different long- run trajectories and illuminates both the brilliance and the limitations of Smith’s conjectural history."

Also see his Twitter thread

"The paper (https://markkoyama.github.io/papers/Public_Choice_Submission%205.pdf) revisits Smith's Book III on how towns drove Europe's movement out of feudalism. Barry Weingast and others have highlighted the implicit game theory: medieval towns allied with kings to break the power of feudal lords.

Smith saw medieval Europe as a three-way struggle: kings, lords, and towns. The king-town alliance emerges when towns are rich enough to offer fiscal and military support, but lords remain a serious threat. I formalize this in a simple game.

The main insight: this is an equilibrium -- but just one of several. Smith's story fits France under Philip Augustus. But history also produced two other coalitions.

Lords and towns allied against tyrannical kings -- the Magna Carta crisis of 1215. And kings allied with lords against towns -- as when Frederick II sacrificed German urban liberties to buy princely support for his Italian campaigns.

Making the model dynamic: the king-town alliance is self-undermining. As commerce grows, lords spend their military capacity on luxuries -- Smith's "diamond buckles" argument. Lords become irrelevant and the game collapses into royal absolutism.

In contrast, the king-lords equilibrium is self-reinforcing. Suppressing commerce keeps towns weak, which keeps the coalition attractive. A poverty trap: towns that start weak stay weak, lords that start strong stay strong. This fits the "second serfdom."

Small differences in initial conditions generate dramatically different long-run trajectories. Western Europe's towns were just developed enough by the 11th-12th centuries. The Commercial Revolution pushed them across the threshold. Eastern Europe didn't cross it.

The framework highlights how "critical junctures" -- the Commercial Revolution, the Black Death, succession crises -- can tip polities from one equilibrium to another. Then self-reinforcing dynamics take over.

Smith's conjectural history is remarkably insightful -- but incomplete. He identified the king-town equilibrium and its self-undermining dynamics. This was one path among several, explaining why Europe's political trajectories diverged so dramatically.

This paper shows how Smith can be still be an input into an active research agenda in economic history (as opposed to simply rehashing old debates)."

Other history related posts:

When Beer is Safer than Water: Beer Availability and Mortality from Waterborne Illnesses in 18th Century England 

Extractive Taxation and the French Revolution: Between 1750 and 1789, areas in France with heavier tax burdens experienced significantly more riots 

MONKS, GENTS AND INDUSTRIALISTS: THE LONG-RUN IMPACT OF THE DISSOLUTION OF THE ENGLISH MONASTERIES 

Did Tea Drinking Cut Mortality Rates in England?

Pre-market societies could sometimes have alot of violence

Did the industrial revolution cause children to take on adult roles later and later? 

Primitive communism: Marx’s idea that societies were naturally egalitarian and communal before farming is widely influential and quite wrong (plus Ruth Benedict on property rights)  

When workers were paid twice a day and given half-hour shopping breaks (Germany, 1923) 

Economics influenced the spread of viral rumors during the French Revolution 

Tuesday, May 12, 2026

The Seasonally Adjusted CPI Was up 0.64% in April

Here are the changes in the seasonally adjusted CPI for the six months ending in March: 

Sept. 0.2951% (There was no report for October due to the government shutdown)
Nov. 0.2523% (change from Sept)
Dec. 0.2978%
Jan. 0.1708%
Feb. 0.2670
March 0.865% 
 
The last decline was June 2024 when it was -0.042%.

See Consumer Price Index for All Urban Consumers: All Items in U.S. City Average from FRED (Federal Reserve Economic Data) compiled by the Research Division at the Federal Reserve Bank of St. Louis for data on the seasonally adjusted CPI.

That site shows a graph but if you click on the Download button you will get the actual numbers in Microsoft Excel.

The Consumer Price Index for All Urban Consumers: All Items in U.S. City Average (CPIAUCSL) was 332.407 in April and 330.293 in March. Since 332.407/330.293 = 1.0064, that means it was up 0.64%. If we had that every month for 12 months it would be up 7.96%.

It was 320.302 in April 2025. Since 332.407/320.302 = 1.0378, that means it was up 3.78% over the last 12 months.

The non-seasonally adjusted CPI was 333.020 in April and 320.795 in April 2025. That was up 3.81%. So pretty close to the seasonally adjusted CPI. This is still above the Fed's target of 2.0% (although they prefer to use the Personal Consumption Expenditures Price Index which was 3.5% higher in March 2026 than March 2025).

For more information see Consumer prices rose 3.8% annually in April, the highest since May 2023 by Jeff Cox of CNBC. Excerpt:

"Prices that consumers pay for a wide range of goods and services increased at a faster-than-expected pace in April, as another burst in energy prices raised further concerns about inflation’s impact on the U.S. economy.

The consumer price index rose at a seasonally adjusted 0.6% for the month, putting the one-year pace at 3.8%, the Bureau of Labor Statistics reported Tuesday. The monthly rate was as forecast, but the annual rate was 0.1 percentage point above the Dow Jones consensus.

Excluding food and energy, the core CPI increased 0.4% and 2.8%, respectively, keeping inflation well above the Federal Reserve’s 2% goal as the monthly rate was the highest since January 2025. Fed officials consider core a better indicator of longer-term inflation trends.

The annual headline inflation rate was the highest since May 2023 and was up half a percentage point from March. Core inflation rose 0.2 percentage point annually."

The article also discusses what types of products are going up in price and what is going down. There is a graph of the monthly year-over-year percent change in prices and core prices going back almost 4 years.   

Related material: 

Consumer Price Index for All Urban Consumers: All Items Less Food and Energy in U.S. City Average (CPILFESL) This is also from from FRED (Federal Reserve Economic Data), compiled by the Research Division at the Federal Reserve Bank of St. Louis. It has the seasonally adjusted core CPI.
 
 
 
The Bureau of Labor Statistics makes seasonal adjustments. See Consumer Price Index Summary.
 
The table below has the annual inflation rate since 1914 in the columns labeled CPI %Ch. or CPI percentage change. It is from Consumer Price Index Data from 1913 to 2026 and is not seasonally adjusted. It is also the December to December change in the CPI. That site also looks at how the 12 month average for the CPI changed from one year to the next.
 

Year

CPI %Ch.

 

Year

CPI %Ch.

 

Year

CPI %Ch.

 

Year

CPI %Ch.

1914

1

 

1944

2.3

 

1974

12.3

 

2004

3.3

1915

2

 

1945

2.2

 

1975

6.9

 

2005

3.4

1916

12.6

 

1946

18.1

 

1976

4.9

 

2006

2.5

1917

18.1

 

1947

8.8

 

1977

6.7

 

2007

4.1

1918

20.4

 

1948

3

 

1978

9

 

2008

0.1

1919

14.5

 

1949

-2.1

 

1979

13.3

 

2009

2.7

1920

2.6

 

1950

5.9

 

1980

12.5

 

2010

1.5

1921

-10.8

 

1951

6

 

1981

8.9

 

2011

3

1922

-2.3

 

1952

0.8

 

1982

3.8

 

2012

1.7

1923

2.4

 

1953

0.7

 

1983

3.8

 

2013

1.5

1924

0

 

1954

-0.7

 

1984

3.9

 

2014

0.8

1925

3.5

 

1955

0.4

 

1985

3.8

 

2015

0.7

1926

-1.1

 

1956

3

 

1986

1.1

 

2016

2.1

1927

-2.3

 

1957

2.9

 

1987

4.4

 

2017

2.1

1928

-1.2

 

1958

1.8

 

1988

4.4

 

2018

1.9

1929

0.6

 

1959

1.7

 

1989

4.6

 

2019

2.3

1930

-6.4

 

1960

1.4

 

1990

6.1

 

2020

1.4

1931

-9.3

 

1961

0.7

 

1991

3.1

 

2021

7

1932

-10.3

 

1962

1.3

 

1992

2.9

 

2022

6.5

1933

0.8

 

1963

1.6

 

1993

2.7

 

2023

3.4

1934

1.5

 

1964

1

 

1994

2.7

 

2024

2.9

1935

3

 

1965

1.9

 

1995

2.5

 

         2025    

          2.7

1936

1.4

 

1966

3.5

 

1996

3.3

 

 

 

1937

2.9

 

1967

3

 

1997

1.7

 

 

 

1938

-2.8

 

1968

4.7

 

1998

1.6

 

 

 

1939

0

 

1969

6.2

 

1999

2.7

 

 

 

1940

0.7

 

1970

5.6

 

2000

3.4

 

 

 

1941

9.9

 

1971

3.3

 

2001

1.6

 

 

 

1942

9

 

1972

3.4

 

2002

2.4

 

 

 

1943

3

 

1973

8.7

 

2003

1.9

 

 

 

 
Here is a timeline graph of this data: