NATURAL CYCLES OF IMITATION AND INTELLECTUAL PROPERTY INFRINGEMENTS

Mark Carlson and Pawel Dyczewski

University of California at Berkeley

 

Abstract

The following model analyzes the problem of imitation and intellectual property rights infringements in developing countries. Specifically, starting from microfoundations the model predicts a gradual decrease of imitation and IPR violations in these countries. The unique contribution of this model is that its results are driven by market forces rather than Intellectual Property Rights.

Introduction

Reducing intellectual piracy is a major concern of the developed world. Most of the economic literature focuses on using stronger laws and enforcement techniques to accomplish this. We believe that there may be other forces, especially in the developing world, that are instrumental in reducing intellectual piracy. One stylized fact to consider is that the piracy rates for some developing countries were found to decline despite no increase in protection or enforcement. For example a study conducted by the International Intellectual Property Alliance (IIPA) found that the piracy rates for computer business applications software in Poland for years 1995-1997 were 75%, 73% and 61% respectively. This decrease in the piracy rates occurred despite the IIPA’s finding that there was no increase in the enforcement of Polish copyright laws.

In this paper, we introduce a model where firms of developing nations start with a large profit incentive to copy the products of the developed nation. Copying is simply cheaper than innovating. Nevertheless copying does have some drawbacks. The pirating firm is restricted to the domestic market. The longer the developing countries’ firms continue to copy, the more difficult it is to copy more advanced goods. Profits from copying thus decline quickly. At some point, the returns to selling a new good to the world market becomes large enough that it overwhelms the remaining incentives to copy and the firm shifts to research and development. This reasoning explains why piracy is significantly smaller in the developed nations. Piracy is only really advantageous if the pool of goods that can be copied is large enough to allow the imitating firm to copy many goods each period, for several periods. Firms in the developed nations, who are on the technological frontier, have only a few goods they could copy. The profits they could make by copying these goods are significantly smaller than those they could make by engaging in innovation.

Model

The Basics:

The model we use follows Romer (1990) with various modifications.

The model has two countries – a developed "North" and a developing "South". We are concerned with the number of different goods these two countries know how to construct. We refer to the number of goods in the North as AN and the number in the South as AS. In order to manufacture a good a country needs to have instructions about how to make that good – a "blueprint". This does not require that the country actually have the knowledge to produce the blueprint from scratch, stealing someone else’s blueprint is a perfectly acceptable way of learning how to produce a good. Our initial condition is that AS is a subset of AN.

In each country the setup is essentially the same. There is a final goods industry that produces output according to the function:

Where A can be either AS or AN, L is labor, and x(i) are capital goods. We assume b <1. Since output is a single good, we treat this sector as if it consisted of a single representative price taking firm.

There is also an intermediate goods sector that produces capital goods. Each firm (i) in the capital goods sector produces a unique, non-depreciating capital good, which it rents to the final output sector. Capital goods are produced using some fraction of output:

Where h i is significantly less than one. We assume that h i is the same for all intermediate firms.

There is also a research sector. The research sector is capable of producing blueprints for goods that are not yet in production. In each country there are J firms that are capable of producing new goods. These firms employ a fixed amount of labor. The firms are however allowed to allocate this labor toward a number of different projects. Each project costs some amount(d ). There are diminishing returns to spreading out the labor supply over a number of research projects. We let vji denote the number of attempts that firm j makes to learn how to produce a new good. The number of successes is taken to be ln(vji) +1.

If one country has a blueprint for a good and the other country does not then the research sector is able to attempt to imitate or copy that good. Ease of copying depends on how many goods the other country knows how to produce relative to yours. One can think about this in two ways. One possibility is that goods that are closer to the technological frontier are harder to reverse engineer and require more knowledge and skill on the part of the imitator to reproduce. Another possibility is that one does not want to copy every good, only goods that will sell well in your country. Thus the more goods you have to choose from, the easier it is to find one that will sell. The firm hires the same amount of labor as if it were innovating. The firm can again distribute the number of workers amongst a variety of projects each costing some amount (f ). We assume that each research firm can engage in imitating as many goods as it wants, though there are again diminishing returns to number of attempts. Cost will also depend on the knowledge ratio (AN/AS). In addition we assume that some firms are better than copying than others. For this reason we introduce g which is a constant that varies by firm and is "distributed" uniformly over the interval [1,2]. We let the number of projects that the firm opt for to be vjc and the number of success to be ln(vjc) +1.

Interactions Amongst Actors: We assume that both countries strictly enforces domestic patent laws for blueprints. This implies two things. First a country will not allow its capital-producing firms to purchase a copied blueprint if the original blueprint was produced domestically. Second it implies that capital goods that are produced

with copied blueprints are not imported if the original blueprint was produced

domestically. We also assume that the North enforces international patent laws, which means that its research firms are barred from copying blueprints from the South.

There is no collusion between any firms.

The intermediate good producers rent their capital goods to every final goods producer they can. If the capital good was produced from an innovated blueprint then they can rent it to final goods producers in both countries. If the capital good was from a

copied blueprint, which only occurs in the South, then it can only be rented in the domestic market. If the blueprint is copied then the resulting capital good is rented at just under the price it would be rented by the firm that bought the original blueprint. The firms producing capital goods command a monopoly on those goods and thus charge monopoly prices to final goods producers.

Firms developing knowledge sell it to the capital goods producing firms. Research firms realize that they are the only ones who are able to sell a particular idea to a capital-producing firm. Research firms also realize that the capital producing firms have a monopoly on the capital goods, so the knowledge producing firms charge a price equal to the monopoly rents the capital firms would realize for use of a blueprint.

Innovated blueprints have an infinite patent protection. Copied blueprints have no protection. Once a good has been copied by one research firm, it may

be costlessly copied by another research firm the next period, which it can then sell to another capital goods firm. The two capital goods firms then compete using Bertrand competition and force profits to zero. Thus, the capital firm

buying the first copied blueprint is only able to receive monopoly profits for one period. This is then reflected in the price it pays to the research firm it buys the copied blueprint from.

Research firms are restricted to either copying or innovating.

Wages and population are fixed.

Capital Firms:

We begin by looking at the profits that the capital goods producing firm is able to realize. In this one sector economy one unit of intermediate goods is produced from h units of output goods. The intermediate firm must "borrow" the output goods from the general public at rate r.

We start deriving the monopoly profits for the capital goods firm by looking at the monopoly profit function for the firm:

We take the derivative of profits with respect to output. We solve for price of output in terms of the elasticity of price of the intermediate good with respect to output of the intermediate good (e ). Doing this we get:

We then find this elasticity by minimizing the cost function of the final goods producing firm with respect to xj

subject to

Noting that the the final goods producer takes p(xj) as given. We solve this result for p(xj) and find that it equals:

Using this equation we are able to solve for the elasticity above. Once we do this and substitute into the price equation we find that the price that the intermediate firm will charge for rental of its intermediate good is

The price of capital good is then fixed. Profits then vary only by the amount of the good that one is able to sell. This is determined by size of the final goods market and is presumed known by all firms in the economy. We make the assumption that the size of the market is the same in both countries. Thus firms selling copied goods make half the profit of a firm selling an innovated good each period.

One period profit for a copied capital good is then:

Profits from innovated blueprints are then more complex. We look at the developing country first. A capital good producing firm here is able to sell its goods to both countries forever. Thus we find profits to be:

Profits in the developing country depend on how long the capital goods firm is able to sell its product in the developing country. We call this time T. Using some inverse sampling with replacement theory we could derive an expression for this, but for now we are content to leave it unknown. We understand that T increases as the amount of research in the developing country increases and T decreases as the amount of copying in the developing country increases. Thus profit is:

Research Firms:

Research firms that are engaged in copying will charge a price (pc) =p c. They must pay their workers the going wage (w). They face a profit function:

where the firm chooses vjc. Taking the first order conditions and solving we find that the optimal choice of vjc is:

Firms that are engaged in innovation are able to charge a price (pi) =p i. They face a profit function:

And their optimal choice of vji is:

Implications:

It is possible that to solve the model for a steady state in which research occurs in both countries and there is a steady state growth rate. This we leave for somebody else, rather we are interested in the transition dynamics that involve shifting between imitation and innovation.

Our first observation is that the profits to the research firm involved in innovation in the developing country are time invariant.

Our second observation is that as the ratio (AS/AN) increases, profits to the imitating research firm also decline. For this section, unless noted, we let A=(AS/AN).

We start with the profit function and expand it to exogenous variables:

Take the derivative with respect to A:

And find profits to copying are always decreasing as the South catches up in blueprints. Now we simply need to show that the south successfully researches more blueprints each period.

First we need to find the ratio of blueprints A where firms switch from

copying to innovating. We start by setting the profits equal so the firm is indifferent between activities.

Simplifying we get:

Now for our final step we show that the South produces at least as many blueprints as the North. We sum output of blueprints (through innovation or copying) over all J firms in each country. We let j be the number of firms in the South that have switched to innovating.

We substitute our solution for A and simplify the summations:

We know that piS piN but if we reduce piS to piN and show the above statement is true we are still okay and that allows us to simplify the expression to:

Since we know that piS>pc the above equation is true as long as any research firm in the South is engaged in copying and d piS/w>1. The latter term must be true since it equals vij and the log function would produce negative profits if it were less than one. Hence it is most likely greater than one.

With this we have shown that firms in the South that start copying will copy more blueprints each period than the North is able to produce. These research firms will see their profits gradually decline. Eventually the profits will reach the break-even point and the firms will begin innovating.

Empirical Tests and Results:

Our model predicts that a firm will switch from copying to innovating as its profits fall. The number of pirated goods will increase but at a slower and slower rate. The number of innovated blueprints produced is increasing at a faster and faster rate. Thus the fraction of goods being sold on the market produced using pirated blueprints (number from pirated blueprints/all goods) should decrease. We will call this fraction the piracy rate for the remainder of the section. We structure the fraction like this because, the IIPA publishes rates of piracy for a variety of markets using this fraction as its rate. We use this data to test our model.

We also need to find a proxy for the number of goods that a country knows how to produce. This is the really difficult part. For our preliminary analysis we use GDP per capita as a proxy. It seems quite reasonable that as the number of goods a country knows how to produce increases that its GDP per capita will increase as well. We use GDP per capita converted to constant 1987 dollars using Purchasing Power Parity and a deflator.

Reasoning that IPR laws may add to the cost of copying, We also included an general IPR protection index in the regressions. The IPR protection index was borrowed from a comprehensive study done by Walter Park and Juan Carlos Ginarte (Park 1997). The index measures coverage of patent laws, membership in international agreements, protection against loses arising from IPR infringements, and enforcement of the IPR laws.

The model we are estimating is then

Piracy is a percent, multiplied by one hundred. The IPR index ranges from 0 (no protection) to 5 (very protected). GDP per capita is in dollars per person. All data are for the year 1995, except the IPR index which is for 1990. We expect to find that the coefficients on both the IPR index and GDP per capita are negative and significant. The results are found in Table 1.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 1

Piracy Rate Regressions

Software

Business

Entertainment

Records

Applications

Software

Video

& Music

CONSTANT

97.3

87.3

109.6

60.3

Standard error

4.34

9.25

9.44

12.22

t stat.

22.38

9.43

11.61

4.92

IPR Index

-1.76

2.24

-6.04

1.12

Standard error

2.75

6.11

5.97

7.87

t stat.

-0.642

0.367

-1.01

0.143

GDP per capita

-0.002

-0.0037

-0.0055

-0.0037

Standard error

0.0005

0.0010

0.0011

0.0015

t stat.

-4.83

-3.70

-5.078

-2.52

N

28

20

28

26

Adjusted R2

.63

.45

.67

.25

The coefficient on GDP is what we expect, negative and significant. The economic magnitude of these coefficients also seems reasonable large. An increase of GDP per capita of $1000 dollars decreases piracy of entertainment software by 3.7 percentage points.

An interesting and surprising result is that the IPR index seems to be statistically insignificant. The following quote from the IIPA report on pirating in Hong Kong provides some insight into why this might be.

A particularly target-rich environment is the notorious Golden Shopping Arcade (GSA), where dozens of small shops do a brisk trade in pirated video games, business software, and computer-related books. GSA has developed a worldwide reputation as a pirate software bazaar, and is even listed in Hong Kong guidebooks as such. In the past, enforcement efforts against GSA vendors were sporadic and had little long-term effect. Last September, BSA, in cooperation with Hong Kong Customs, employed a new legal tactic against GSA pirate retailers. BSA [Business Software Alliance] obtained civil injunctions against 22 vendors for sales of pirated software. Faced with the threat of contempt proceedings for further violations, many shops closed down, and pirate sales of software of BSA member companies at GSA declined dramatically. When stores -opened, Customs followed up with increased raiding activity. As a result, sale of pirated business software at GSA was driven underground, where efforts to infiltrate pirate distribution networks continue; a major Customs raid at GSA on February 10-11 netted 13,000 pieces of pirated software. However, many vendors may have resumed operations at other locations; Hong Kong Customs has identified more than 20 other shopping arcades in Hong Kong where pirated software is produced.

The following graphs ploy the relationship between GDP per capita and piracy. They use data for 1995-1997. The strong correlation of piracy rates and GDP per capita is also visible on the following graphs. Both of the graphs have a line of best fit. Graph 1 gives some general evidence of the relationship between the GDP per capita and the piracy rates for business software. Graph 2 presents similar evidence for the records and music industry.

 

 

Graph 1

 

Graph 2

 

Alternative evidence on the model is provided using data complied by the World Bank. The World Bank publishes a cross-country data on royalties paid and received by different countries. Royalty and license fees are payments and receipts between residents and nonresidents for the authorized use of intangible, nonproduced, nonfinancial assets and proprietary rights (such as patents, copyrights, trademarks, industrial processes, and franchises) and for the use, through licensing agreements, of produced originals of prototypes (such as manuscripts and films).

The levels of international royalty receipts should be positively related to the level of innovations for a given country. Hence, if our model is correct, the royalty receipts should be highly correlated with GDP per capita corrected for IPR laws. Since we are dealing with amounts here and not percentages we should correct for size of the country. To do this, we use size of urban population.

Our regression model is then

All observations are for 1995.

Table 2 presents the results.

 

Table 2

Dependent Variable: Royalty Receipts

(Millions of Dollars)

Parameter

Standard

t statistics

Variable

Estimate

Error

INTERCEPT

-325.4

260.1

-1.25

IPR

-9.28

160.2

-0.058

GDP PER CAPITA

.066

0.033

2.031

URBAN POPULATION

2.032

1.86

1.094

N

20

Adjusted R2

.24

 

The regression results suggest that GDP per capita is a significant factors affecting royalty receipts. This lends some support to our idea that the number of innovated products that can be sold abroad increases as the number of goods one knows how to make increases.

In an effort to find a better proxy for the number of goods a country knows how to produce, we consulted the United Nations International Yearbook Industrial Statistics. We looked at the publishing industry. The UN publishes data on number of firms engaged in publishing/printing. The IIPA publishes data on the losses to US publishers resulting from copying of the books abroad. We believe that the number of publishers per capita should increase as the number of goods the country knows how to make increases. Moreover we expect this proxy to increase more directly with number of ideas than GDP per capita.

Since we are again dealing with an amount, we want to correct for country size using urban population. Here we also check for non-linearity in our proxy, by including a square. We also include an interaction term between GDP per capita and Urban Population. We do this because want to correct for the possibility that richer urban populations have more money, and thus may either buy more pirated goods, or may spend more on a non-pirated good as a prestige item. Regretfully the number of countries for which we have both the number of publishers and the IPR index is very small. So for this regression we drop the IPR index. The model we estimate is then:

The data are again for the year 1995, except publishers, for whom the most recent data was 1993. We expect that publishers per capita will be negatively correlated with the losses to foreign country arising from copying.

The table 3 presents the results of such regression:

Table 3

Dependent Variable: Loss to U.S. publishers from pirates (in millions of dollars)

VARIABLE

PARAMETER ESTIMATE

STANDARD ERROR

T STATISTICS

INTERCEPT

6.74

3.064

2.189

PRINT SHOPS PER CAPITA

-0.046

.023

-1.939

GDP PER CAPITA

-.0007

0.001

1.37

URBAN POPULATION

0.39

0.032

11.88

TRUNK DUMMY

-3.9

3.71

-1.053

YEAR DUMMY

-0.8

2.85

-0.28

(PRINT SHOPS PER CAPITA)^2

0.00005

0.000028

1.86

GDP PER CAPITA*URBAN POPULATION

.00002

.000021

1.0

N

17

Adjusted R2

.96

As expected, publishers per capita variable turns out to have a negative correlation with the dependent variable although the correlation is statistically significant only at 90% confidence level. Again we believe this to be yet another piece of evidence supporting our thesis.

Plans For Further Research:

Our first priority is to expand and enrich the empirical section. As they stand, our empirical results are suggestive but far from conclusive. Unfortunately, testing or finding data to support a model dealing with piracy is rather difficult. Suggestions in this area would be greatly appreciated.

The model we use in this paper is quite versatile and it can be used as a foundation to approach other questions.

First we would like to expand the variety of goods that we are able to discuss. The current model is best suited for low capital goods that are easy to reverse engineer. We plan to develop the model to include goods that require accumulation of knowledge, human capital and/or physical capital. We expect that the resulting dynamics between the current sector and new sector will help us understand some of the issues faced in the industrialization process.

Separating legal imitation from illegal imitation is also important. Industrializing nations as part of their catch-up process often uses legal imitation. Developing nations purchase the license to produce goods the are slightly obsolete in the developed world. In this way developing countries are able to learn how to construct these good more easily than they could on their own. This process however does not infringe on the rights of and is not detrimental to firms in the developed world. This form of interaction between developed and developing worlds is common and important. The amount of this form of imitation probably parallels the amount of piracy, but we should have a model in order to more fully understand the economic options for firms in the developing countries.

Finally we hope to bring IPR laws into the model more explicitly and endogenize them. We suspect that a country is only really likely to introduce and enforce IPR laws once firms in the country begin to innovate. We further suspect that international IPR laws are passed only after the country begins to export large amounts of goods. It seems likely that countries find that it they do not want their innovated goods copied, then they must respect the patents of others.

Including these ideas would create a much richer model.

Conclusion:

In this paper, the idea that profits from piracy must be considered when discussing international protection of Intellectual Property has been introduced. A model is presented that shows how changing profits may result from the catching up process and in turn affect the amount of piracy. The end result is that piracy may fade without significant action on the part of the government. We then provide empirical results that suggest that this line of reasoning may indeed be important.

 

 

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