Gerschenkron effect

What Is Gerschenkron Effect?

The Gerschenkron effect refers to the phenomenon where changing the base year used in calculating an index number for aggregated output or economic activity significantly alters the measured growth rate. This effect is primarily observed in fields of economic measurement and statistical analysis, highlighting a potential bias that can arise when constructing economic indices over time or across different entities. It suggests that if an earlier period's prices are used as weights, the calculated growth often appears higher than if later prices are used, especially when there's significant technological progress and corresponding changes in relative prices and quantities²¹. The Gerschenkron effect underscores the complexities involved in accurately measuring economic growth and output.

History and Origin

The Gerschenkron effect is named after Alexander Gerschenkron (1904–1978), a prominent economic historian and professor at Harvard University. ²⁰Gerschenkron first identified this statistical bias in his 1947 article, "The Soviet Indices of Industrial Production," where he analyzed the official Soviet industrial output figures from 1927–1937. He¹⁷, ¹⁸, ¹⁹ demonstrated that the remarkably high rates of growth reported for Soviet industrial production were, in part, an outcome of an index number problem.

G¹⁶erschenkron showed that if a Laspeyres index, which uses base-period weights, was applied to the Soviet data, it significantly overstated the real expansion, particularly due to the rapid growth of new, lower-priced products that had small weights in the early base period. Hi¹⁵s work challenged the prevailing understanding of Soviet economic performance and became a significant finding in economic statistics and comparative economic systems. The effect is also broadly linked to his broader theory of economic development, where he posited that "latecomer" countries could experience more rapid industrialization by adopting advanced technologies already developed by pioneers.

#¹³, ¹⁴# Key Takeaways

• The Gerschenkron effect highlights a measurement bias in aggregated economic indices due to the choice of the base period for weighting prices.
• It typically manifests when there is a negative correlation between changes in prices and quantities, meaning goods whose prices are falling tend to have increasing production volumes.
• Using an "early-weighted" index (like a Laspeyres index) can lead to an overstatement of growth compared to a "late-weighted" index (like a Paasche index).
• The effect has implications for both inter-temporal (over time) and inter-spatial (across countries) comparisons of economic aggregates.
• It emphasizes the importance of understanding the methodology and underlying data when interpreting reported economic statistics.

Formula and Calculation

The Gerschenkron effect itself is not a direct formula but rather an observed outcome of how different index number formulas behave when relative prices and quantities change significantly over time. It can be understood as the difference in the measured growth rates derived from a Laspeyres quantity index and a Paasche index.

A Laspeyres quantity index (L) uses base period prices ($P_0$) to weight quantities:

Where:

• $P_{0i}$ = price of good i in the base period
• $Q_{0i}$ = quantity of good i in the base period
• $Q_{1i}$ = quantity of good i in the current period

A Paasche quantity index (P) uses current period prices ($P_1$) to weight quantities:

Where:

• $P_{1i}$ = price of good i in the current period
• $Q_{0i}$ = quantity of good i in the base period
• $Q_{1i}$ = quantity of good i in the current period

The Gerschenkron effect arises because, in many cases, goods that experience rapid growth in quantity (e.g., due to innovation or increased productivity) also experience a relative decline in price. When an early-weighted (Laspeyres) index is used, these rapidly growing, now cheaper, goods are weighted by their higher base-period prices, inflating the overall growth estimate. Conversely, a late-weighted (Paasche) index would assign lower current prices to these goods, resulting in a lower measured growth rate. Th¹²e "effect" essentially measures the discrepancy or bias between these two approaches.

Interpreting the Gerschenkron Effect

Interpreting the Gerschenkron effect involves understanding how the choice of a base year influences economic comparisons. If a country or sector experiences significant structural transformation, with new industries or products emerging and older ones becoming less dominant, the effect becomes more pronounced. For instance, if an economy rapidly expands production of new, technologically advanced goods whose relative prices are falling, using an older base year for calculating output indices will assign a higher weight to these goods than their current prices would warrant. This leads to an overestimation of the true economic growth.

Conversely, if a more recent base year is chosen, the measured growth might appear lower because the new, cheaper goods are weighted by their lower current prices. This phenomenon is critical in assessing the actual performance of developing economies or those undergoing rapid industrial change, where shifts in price structure and quantity structure are common.

Hypothetical Example

Consider a hypothetical country, "Innovia," which in 2000 produces two main goods: traditional textiles and emerging high-tech gadgets.

Calculate using 2000 as the Base Year (Laspeyres Index):

• Value in 2000: (100 units * $10) + (10 units * $100) = $1,000 + $1,000 = $2,000
• Value in 2010 at 2000 prices: (90 units * $10) + (200 units * $100) = $900 + $20,000 = $20,900
• Growth (2000 Base): ($20,900 / $2,000) = 10.45, or 945% growth.

Calculate using 2010 as the Base Year (Paasche Index for comparison):

• Value in 2010: (90 units * $12) + (200 units * $50) = $1,080 + $10,000 = $11,080
• Value in 2000 at 2010 prices: (100 units * $12) + (10 units * $50) = $1,200 + $500 = $1,700
• Growth (2010 Base): ($11,080 / $1,700) = 6.517, or 551.7% growth.

In this example, the growth rate of Innovia's output between 2000 and 2010 is significantly higher when calculated using the 2000 base prices (Laspeyres index) compared to using 2010 prices (Paasche index). This discrepancy is a clear illustration of the Gerschenkron effect. The high-tech gadgets experienced massive industrialization growth in quantity while their relative prices fell. The older base year assigns a higher initial weight to these rapidly expanding, now cheaper, goods, leading to an exaggerated growth figure.

Practical Applications

The Gerschenkron effect has important practical applications in economic analysis, particularly in areas involving cross-country comparisons and historical economic data.

• International Comparisons: When comparing the Gross Domestic Product (GDP) or productivity across countries, especially those with different stages of economic development or differing economic structures, the Gerschenkron effect can lead to biases. For example, methods that use a common set of international prices for comparison can show an overvaluation of a poorer country's real GDP if the reference price structure deviates significantly from its own. Th¹¹is is particularly relevant for organizations like the World Bank and OECD when conducting Purchasing Power Parity (PPP) comparisons.
• Historical Economic Analysis: Economic historians must be acutely aware of the Gerschenkron effect when analyzing long-term trends in output, especially during periods of rapid structural change, such as the Industrial Revolution or the rise of new sectors (e.g., information technology). Using outdated base years can distort the actual pace of economic growth and structural shifts.
• Policy Making: For policymakers in developing countries, understanding the Gerschenkron effect highlights the strategic importance of technology adoption and investment in human capital goods to accelerate industrialization. Ho¹⁰wever, it also cautions against interpreting raw growth figures without considering the underlying statistical methodologies. The effect reminds analysts to scrutinize the methodologies of national accounts when assessing economic performance and making policy decisions based on aggregated data.

Limitations and Criticisms

While providing a crucial insight into index number bias, the Gerschenkron effect is not without its limitations and has faced criticisms. Some economists argue that if production is "properly measured" in terms of "real" economic output (i.e., adjusted for inflation and changes in value), the Gerschenkron effect should not exist. Th⁸, ⁹e core of the criticism often lies in the definition of "real" output and whether traditional fixed-weight indices truly capture the evolving nature of an economy.

One common critique suggests that the Gerschenkron effect is not an inherent economic phenomenon but rather a measurement artifact, specifically an "index-number problem," rather than a true aggregation issue. St⁷efano Fenoaltea, for instance, argues that the "Gerschenkron effect" as a "snare and delusion" if one properly understands "real" measurement in economics, suggesting that the issue arises from a metaphorical, rather than literal, interpretation of "real" terms.

F⁶urthermore, while the effect was very visible in early international comparisons (e.g., in the 1970s and 80s for poorer countries relative to the OECD), more recent analyses suggest the effect has significantly weakened due to global economic shifts, such as the increased influence of economies like China and India on international price vectors, and the convergence of price structures through increased international trade. Th⁵is suggests that while historically significant, its practical magnitude may vary depending on the specific economic context and the statistical methods employed.

Gerschenkron effect vs. Index Number Problem

The Gerschenkron effect is often confused with, or seen as a specific manifestation of, the broader index number problem. The index number problem refers to the general challenge of accurately measuring changes in aggregate economic quantities (like output or cost of living) over time or across different locations when the relative prices and quantities of individual components are also changing. It⁴ arises because there is no single, unequivocally "correct" way to average or weight diverse goods and services.

The Gerschenkron effect specifically describes a particular type of bias within this larger problem: the tendency for "early-weighted" aggregate indices (e.g., using a Laspeyres index with an older base year) to show higher rates of growth than "late-weighted" aggregate indices (e.g., a Paasche index with a more recent base year), especially when there's a strong negative correlation between price changes and quantity changes (e.g., rapid production increases for goods whose relative prices are falling due to technological progress). Thus, while all instances of the Gerschenkron effect are examples of the index number problem, not all index number problems necessarily exhibit the specific bias described by the Gerschenkron effect.

FAQs

What is the main idea behind the Gerschenkron effect?

The main idea is that the choice of the base year (or weighting period) for an economic index can significantly influence the calculated growth rate, often leading to an overestimation of growth if an older base year is used, especially for industries with rapid innovation and falling prices.

#³## Who was Alexander Gerschenkron?
Alexander Gerschenkron was an American economic historian born in the Russian Empire (now Ukraine) who became a professor at Harvard University. He is known for his work on economic development and for identifying the index number bias known as the Gerschenkron effect.

#²## How does the Gerschenkron effect impact measuring GDP?
When calculating Real GDP, the Gerschenkron effect implies that using an older base year for prices can inflate the measured growth if the economy has experienced significant structural changes with new goods becoming cheaper and more abundant. This can make a country appear to have grown faster than it would if a more recent base year were chosen.

Is the Gerschenkron effect still relevant today?

Yes, the Gerschenkron effect remains relevant, particularly in international economic comparisons and historical analysis, although its magnitude might have diminished in some contexts due to globalization and changes in statistical methodologies. It highlights the importance of understanding the underlying data and weighting schemes in any aggregated economic statistic.¹