The price of oil and structural change
Searching for Stolper Samuelson-effects in the Norwegian economy from 1992 to 2013
Marte Ragnhild Owren Claussen
Thesis for the Master of Philosophy in Economics Department of Economics
UNIVERSITY OF OSLO
May 2016II
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The price of oil and structural change
Searching for Stolper Samuelson-effects in the Norwegian
economy from 1992 to 2013
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© Marte Ragnhild Owren Claussen 2016
The price of oil and structural change. Searching for Stolper Samuelson-effects in the Norwegian economy from 1992 to 2013.
Marte Ragnhild Owren Claussen http://www.duo.uio.no/
Trykk: Reprosentralen, Universitetet i Oslo
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Summary
In this thesis I investigate whether there can be found traces of effects predicted by the Stolper Samuelson theorem to follow from changes in the price of oil in the Norwegian economy, between 1992 and 2013. Although fluctuating, the price of oil had an increasing trend from around the new millennium until 2013. According to the Stolper Samuelson theorem, the returns to the factor used intensively in the production of a good will increase if the price of that good increases. This factor price increase is induced by the product price increase and enhanced by the process of structural change following the product price increase.
The main focus of the thesis is on the structural change predicted by the theorem to follow from changes in the oil price. I look at the development of the employment in the petroleum sector as well as the development of the employment that can be directly and indirectly attributed to petroleum activities through deliveries to the petroleum sector. In order to identify the development in direct and indirect employment, I conduct estimations using input-output tables for domestic production and data on employment in most sectors of the economy.
I find that the developments in employment attributable to petroleum activities show traces consistent with the ones predicted by the Stolper Samuelson theorem in the case of an increase in the oil price. The employment attributable to petroleum activities and its relative importance for total employment in the economy has markedly increased over the period studied. The results show less clear traces of effects on employment predicted to follow from a reduction in the oil price. I argue that other factors may also have contributed to the movement of employment towards petroleum related activities over the period studied, one such factor being increased competition from low-cost countries facing the traditional export oriented manufacturing sector.
I also search for traces predicted by the Stolper Samuelson theorem to follow from changes in the oil price on the wage developments of an occupational group recognized to be intensively used in the petroleum sector, namely engineers. Descriptive statistics are applied when investigating this relationship. The analysis shows that clear traces of effects predicted by the theorem are difficult to identify. The wage developments show some traces consistent with the predictions of the theorem in the long run, when the price increases. I argue that several factors other than the price of oil might have affected the wage development of engineers.
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VII
Preface
This thesis marks the end of two years as a master student at the Department of Economics at the University of Oslo.
First of all, I would like to thank my supervisor, Karen Helene Ulltveit-Moe. I am truly grateful for all her valuable advice and guidance through the process of writing this thesis. I would also like to thank Signe Marie Brandal and Marie Brun Landmark for proofreading and for all the motivating conversations throughout this semester.
Finally, I would like to thank Tristan Hauff and my family for all their support and encouragement.
Any errors in the thesis are solely my responsibility.
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Table of contents
1 Introduction ... 1
2 Background ... 3
2.1 The price of oil ... 3
2.2 The petroleum sector and general developments ... 4
2.2.1 The petroleum sector ... 5
2.2.2 Employment in the petroleum sector ... 6
2.3 The supplier industry ... 7
3 The theoretical framework ... 10
3.1 The two- factor, two- good model... 10
3.2 The Stolper Samuelson theorem ... 13
3.3 Discussion of assumptions ... 17
3.4 Review of empirical literature on the Stolper Samuelson theorem ... 19
4 The price of oil and structural change ... 23
4.1 The predictions of the Stolper Samuelson theorem ... 24
4.2 Data and method ... 24
4.3 The developments in employment attributable to petroleum activities and the price of oil ... 27
4.3.1 Employment directly and indirectly related to petroleum activities ... 27
4.3.2 Can the Stolper Samuelson theorem explain the development in employment attributable to petroleum activities? ... 32
5 The wage developments in light of the Stolper Samuelson theorem ... 39
5.1 The predictions of the Stolper Samuelson theorem ... 39
5.2 Data ... 41
5.3 The wage developments ... 43
6 Conclusion ... 51
Bibliography ... 52
Appendix ... 57
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1 Introduction
An important insight from the classical Stolper Samuelson (1941) theorem says that if the price of a good increases, the returns to the factor used intensively in the production of that good will increase. This factor price increase is induced by the product price increase and enhanced by the process of structural change following the product price increase.
From the late 1990s until recent events, the price of crude oil increased sharply, interrupted by decreases in 2000, 2006 and 2008. At the same time, the Norwegian petroleum sector became an increasingly important employer in the economy and the sector affects the rest of the economy through its demand for inputs in production. The fluctuations in the price of oil over this period, and the fact that Norway cannot affect the price because it is determined in the world market, makes this an interesting case for studying Stolper Samuelson effects in the Norwegian economy.
The main focus of this thesis is the process of structural change, predicted by the Stolper Samuelson theorem to be induced by the change in the price of oil. The thesis presents an analysis of the developments in the employment related to the oil and gas sector in Norway, in light of the theorem, from 1992 to 2013.
In particular, I look at the developments of the employment in the petroleum sector as well as the developments of the employment that can be directly and indirectly attributed to petroleum activities through deliveries to the petroleum sector. In order to identify the developments in the employment directly and indirectly attributable to the petroleum activities, I perform estimations using input-output tables for domestic production and data on employment in most sectors of the economy. All calculations are conducted in Microsoft Excel 2010 and an estimation of correlation coefficients is conducted in Stata.
The thesis also looks at the developments of wages for a group of workers recognized to be intensively used in the petroleum sector, namely engineers, in light of the Stolper Samuelson theorem and the developments of the price of oil. Descriptive statistics of wage developments from 2003 to 2013 are applied when investigating the relationship between the oil price and the wages of engineers.
The purpose of the analyses of the thesis is to search for traces of effects on employment and wages predicted by the Stolper Samuelson theorem to follow from changes in the price of oil.
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Chapter 2 provides background information on the developments of the price of oil and some general developments in the petroleum sector and the supplier industry. Chapter 3 presents the Stolper Samuelson theorem and its theoretical framework, which is the Heckscher- Ohlin model of international trade. This chapter also presents a discussion of some of the underlying assumptions of the model and a review of empirical literature on the Stolper Samuelson theorem. Chapter 4 presents the estimations and the analysis of the developments of the employment attributable to petroleum activities in light of the developments in the price of oil. Chapter 5 covers the analysis of the wage developments of engineers in light of the price of oil. Finally, chapter 6 concludes.
3 0
100 200 300 400 500 600 700 800
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010
2 Background
The purpose of this chapter is to provide useful background information for when later in the thesis studying the developments in the employment attributable to petroleum activities and wages, in light of the developments of the price of oil. The chapter includes an overview of the development of the price of oil and ways in which it affects the petroleum sector and the Norwegian economy. I also present an overview of general developments in the petroleum sector, including the developments in employment directly employed in this sector. The chapter also includes a short presentation of the supplier industry.
2.1 The price of oil
Like many other commodity prices, the price of oil is highly fluctuating, and it is determined in the world market. Norway, being a relatively small producer of oil, takes the price as exogenously given. Figure 1 presents the developments in the price of crude oil between 1970 and 2013, in Norwegian Kroners.
Figure 1. The price of crude oil in 2015 Norwegian kroners NOK
Source: Norwegian National Budget 2015
The price of oil shows a steep overall increasing trend since around the new millennium, although interrupted by decreases after 2000, 2006 and 2008. This increasing trend was mainly driven by increased demand from Asia and increasing production costs (Brander, et al., 2013). Especially the strong growth of China was a contributing factor to the increase in demand, which put pressure on the price (Hicks & Lutz, 2013).
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Fluctuations in the oil price affect the Norwegian economy in several ways. Firstly, it affects the profitability of the firms in the petroleum sector, and an increasing oil price typically leads to higher demand for employment and intermediate and investment products. This also affects the activity in the rest of the economy. The increasing price of oil from around the new millennium led to higher investments in the petroleum sector and was a contributing factor to the economic upswing in the Norwegian economy around 2003, after some years with a moderate recession (Eika & Martinussen, 2013; Statistics Norway, 2004). Movements in the price also affect the income that the petroleum sector generates to the Norwegian government.
As a net exporter of oil, Norway is a different exporter than many other countries and its terms of trade are highly connected to the movements in the price of oil. The steep increase in the price of oil during the 2000s was the main contributing factor to the dramatic improvement in Norway’s terms of trade over the same period (Norwegian Ministry of Finance, 2014). The development in the price of oil also affects other economic variables, such as the exchange rate, the expectations of households, as well as Norwegian stocks (Cappelen, et al., 2014).
2.2 The petroleum sector and general developments
The first field of petroleum on the Norwegian continental shelf, Ekofisk, was discovered in 1969. During the startup phase, as Norwegian companies had not yet developed the skills required, the Norwegian government granted licenses to foreign companies who undertook the exploration activities and developed the first fields on the Norwegian continental shelf (Ministry of Petroleum and Energy; Norwegian Petroleum Directorate, 2013). During the first years of exploration and production, most of the resource inputs demanded by the petroleum companies were also imported. Gradually, beginning with the entrance of Norwegian Hydro and the establishment of Statoil in 1972, Norwegian petroleum companies entered the exploration and extraction activities, and the imports of resource inputs started to fall, as more competence was developed in the new supplier industry (Eika & Martinussen, 2013; Ministry of Petroleum and Energy; Norwegian Petroleum Directorate, 2013).
With these developments came new employment opportunities for the Norwegian labor force and the petroleum industry gradually became an important source of direct and indirect employment in the economy.
5 2.2.1 The petroleum sector
Throughout the thesis, if not otherwise specified, I choose to limit the definition of the petroleum sector to include the activities “oil and gas extraction” and “service activities incidental to oil and gas”, defined according to Statistics Norway’s Standard Industrial Classification of 2007 (SIC 2007). Oil and gas extraction can be thought of as the “core”
activity in the petroleum industry, while service activities incidental to oil and gas include activities such as construction of foundations for boreholes, test drilling, geological observations of potential sites and other exploration services. All firms classified as part of one of these categories have the biggest share of their production directed towards petroleum related activities. The firms classified as part of the category “oil and gas extraction” are often referred to as operators1 (Ekeland, 2015).
In 2013, the petroleum sector’s share of GDP, measured in current prices, was 21% - a share which has almost doubled since 19902. Furthermore, exports from the petroleum sector accounted for 50% of total exports of goods and services in 2013, also measured in current prices3.
The production of oil has decreased in volume since 2000. As figure 2 shows, the production of crude oil reached a maximum in 2000, with over 180 million standard cubic meters (Sm3), before it slowly fell towards 2013. However, due to the increasing oil price, the income of the firms in the petroleum sector did not move in the same direction as production, and the gross product of the petroleum sector measured in prices more than doubled between 2001 and 20134 (Midsem, et al., 2015). The increase in profitability was most likely a contributing factor to an increase in demand for labor and intermediate and investment products coming from the petroleum sector over the same period. Even though production was lower, the increased profitability may have given less incentive to e.g. reduce employment. Another reason for the decreasing production, but yet high demand for resources, is thought to be that the petroleum resources left in the ground are more difficult to extract than the resources that
1 I could also have included the activity “transportation via pipelines” in the definition of the petroleum industry.
This category includes activities such as transportation of oil and gas for distribution or to refining plants and the firms in this category also have the biggest part of their production directed towards petroleum activity (Eika, et al., 2010). The way the input-output tables used in the analysis in chapter 4 are structured, the definition stated above is the most suitable one because in the input-output matrices, “transport via pipelines” is classified together with “land transport”, which includes road and railway transportation of passengers and goods.
2 Own calculations based on data retrieved from Statistics Norway.
3 Own calculations based on data retrieved from Statistics Norway.
4 Own calculations based on data retrieved from Statistics Norway.
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0 50 100 150 200
1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013
were extracted first (Eika & Martinussen, 2013). Furthermore, the extraction of gas did not drop after 2000 as extraction of oil did, but continued to increase steadily.
Figure 2. Net production of oil in million SM3 Mill Sm3
Source: Norwegian Petroleum Directorate (Fact pages)
2.2.2 Employment in the petroleum sector
In 2013 the petroleum sector employed 64 300 people directly, which made up 2,46 % of total employment in Norway5. Figure 3 shows the development of this share, which flattened out and even decreased some during the 1990s, and started to increase again around the year 2000. Between 2000 and 2014 the petroleum sector’s share of total employment doubled, before employment in the petroleum sector begun to fall in 2014, after the recent drop in the price of oil.
A fraction of the people employed in the petroleum sector are not registered as residents in Norway, but live abroad and commute to Norway for work. This is possible as the working hours in the petroleum sector are often organized with some weeks on, followed by some weeks off work. In this group of non-residential workers, we find both Norwegian and non- Norwegian citizens. With a broader definition of the petroleum sector, also including
“transportation via pipelines”, “building of oil platforms and modules”, “installation and completion work on platforms and modules” and “supply bases”, Ekeland (2015) estimated the number of these workers to be 5 290 in 2013. With the more narrow definition of the petroleum sector applied here, this number for 2013 will most likely be lower.
5 Own calculations based on data retrieved from Statistics Norway. Total employment in Norway is measured with data from Statistics Norway’s Labor force survey.
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0,0 % 0,5 % 1,0 % 1,5 % 2,0 % 2,5 % 3,0 %
1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 2012
Figure 3. Employment in the petroleum sector as percentage of total employment in Norway Percent
Source: Statistics Norway (Statbank)
2.3 The supplier industry
The petroleum sector’s demand for intermediate and investment goods and services demands the use of labor that can be attributed to petroleum activities outside of what is defined as the petroleum sector, through the production of such goods that are delivered to the petroleum sector. Deliveries to the petroleum sector can be characterized as either direct or indirect. The direct deliveries are delivered directly from a firm outside of the petroleum sector to a firm in the petroleum sector. However, producing deliveries for the petroleum sector requires input in production for the firms producing these, which is provided by other firms that again need inputs in their production, and so on. This chain of sub deliveries is what is referred to as indirect deliveries to the petroleum sector. Labor used in the production of the direct and indirect deliveries to the petroleum sector can be characterized as labor that is directly and indirectly related to petroleum activities.
Figure 4 presents the developments of the petroleum sector’s demand for intermediate inputs and investments in real capital as share of GDP for mainland Norway. Intermediate goods and services are inputs used in the production of the petroleum sector. Investment goods and services are usually defined as goods and services used in the production process, that have a value over a certain amount, and that are expected to last for at least one year (Midsem, et al., 2015). Investments in real capital have fluctuated a lot, with tops in 1985, 1993 and 1998 before the new millennium. After 2002 the investments increased strongly and reached an all- time high with over 200 billion Norwegian kroners in 2014 (Søbye, 2013). This amounted to almost 9% of mainland GDP, as shown in the figure. The petroleum sector’s demand for intermediate inputs grew steadily from the early years of oil and gas extraction, until around
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0 % 1 % 2 % 3 % 4 % 5 % 6 % 7 % 8 % 9 % 10 %
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 Intermediate inputs as percentage of GDP
mainland Norway
Gross investment in real capital as percentage of GDP mainland Norway
2004, when this demand started to grow at a different pace. During this period there was a steeper increase in the use of intermediate inputs as share of GDP of mainland Norway as well, as shown in figure 4.
Figure 4. Intermediate inputs and investments in real capital as percentage of GDP mainland Norway Percent
Source: Statistics Norway (Statbank)
The direct deliveries of intermediate and investment goods and services to the petroleum sector are provided by what is typically referred to as the Norwegian supplier industry as well as some other domestic industries and also through imports. The firms that, in SIC2007, are classified under the categories “building of ships and oil platforms”, “manufacture of machinery and equipment” and “repair and installation of machinery and equipment” are often considered to form the supplier industry because of their large contributions of deliveries to the petroleum sector (Berg, 2015). The first category is one of the most important suppliers of investment goods, while the two others deliver both investment- and intermediate products (Eika, et al., 2010; Berg, 2015).
In addition to the traditional supplier industry, firms providing various services are also important suppliers of intermediate and investment inputs for the petroleum sector. Statistics Norway (2015) and Eika et al. (2010) show that in particular, technical, scientific and business services such as engineering, analysis and ICT services are important direct suppliers. Firms providing financial services are also important suppliers, as well as firms providing wholesale trade services and firms renting and leasing various goods such as transport equipment and machinery.
9 Some of the demand for intermediate and investment products from the petroleum sector is covered through imports. In 2012, the direct imports of intermediate inputs made up 28 % of the petroleum sector’s demand for this type of good6. Midsem et al. (2015) defined the petroleum sector as the two SIC 2007 categories “oil and gas extraction” and “transportation of pipelines” and found that direct imports of investment goods made up 16,4% of their total demand for this type of good in 2012.
6 Own calculations based on Statistics Norway’s input-output table of 2012.
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3 The theoretical framework
To analyze and understand the effect of the oil price on Norwegian employment, industrial structure and wages, I use the Stolper Samuelson theorem, which builds on the classical Heckscher- Ohlin model of international trade. Before proceeding to the analyses I will start by presenting both the Heckscher- Ohlin framework and the Stolper Samuelson theorem.
An ideal model for studying the effects of structural change and changes in wages in the Norwegian economy in light of the development of the oil price would have had three factors of production: capital that is specific to each sector in the short run, human capital that is also specific to each sector in the short run and labor that can move between the two sectors in the short run. Or alternatively, a model that also includes intermediate products as a factor of production. However, the two-sector, two-factor Stolper Samuelson theorem still deliver some important qualitative insights that we can use.
3.1 The two- factor, two- good model
The Heckscher-Ohlin model considers two countries and two goods, where differences in relative factor endowments of the two countries, and different factor intensities in the production of the two goods is the basis for trade. As the focus of the thesis and the Stopler Samuelson theorem is on mechanisms happening inside one particular country, I focus on the framework for one country, and leave the model’s predictions for comparative advantage, specialization and trade in the background. The following presentation of the model is based on Norman and Orvedal (2010, pp. 34-100).
The model is a general equilibrium model, implying that the model considers interactions of all markets and how they affect production, prices and allocation of and returns to production factors. In equilibrium, firms maximize their profit, consumers maximize utility and the markets for the production factors clear.
The model considers a small open economy with perfect competition. The fact that the country is small means that it takes prices as exogenously given. Changes in supply or demand in the country will not affect the world market prices. The country produces two types of homogenous goods, which I will call petroleum, 𝑝, and other goods, 𝑜. The firms in the economy utilize two input factors which are perfectly mobile within the country in the long run. I call these capital, 𝑘, and labor, 𝑙. Each firm produces only one of the goods, so
11 the economy can be divided into two sectors – a “petroleum sector”, and a sector producing other goods, which I call “the rest of the economy”. Furthermore the model assumes constant returns to scale. The production function, 𝑥𝑖 = 𝐹𝑖(𝑘, 𝑙), where 𝑖 denotes the two goods p or o, has positive and decreasing returns in each production factor.
The relative amount of the two production factors needed in production differs between the two goods. This implies that the two sectors differ in their relative use of the production factors. When presenting the Stolper Samuelson theorem in section 3.2 I will look at both the case where the petroleum sector is intensive in capital and the case where it is intensive in labor. However, when presenting the model framework in this section, I assume that the petroleum sector uses capital intensively and that the rest of the economy uses labor intensively. This can be shown as 𝑘𝑙𝑝
𝑝 < 𝑘𝑙𝑜
𝑜, where 𝑘𝑙𝑝
𝑝 is the intensity of labor relative to capital in the petroleum sector and where 𝑙𝑜
𝑘𝑜 is the intensity of labor relative to capital in the rest of the economy. The intensity of labor relative to capital is denoted 𝑎𝑖.
Due to constant returns to scale, the productivity of each unit of production factors is independent of the level of production and the amount of production factors. The productivity of capital depends only on the amount of labor per unit of capital in production, so that
𝑥𝑖
𝑘𝑖 = 𝑓𝑖(𝑎𝑖), where 𝑓′ > 0 and 𝑓′′ < 0. Using this expression, the production function can be rewritten in terms of skill intensity, as
𝑥𝑖 = 𝑘𝑖𝑓𝑖(𝑎𝑖). (1)
From (1) it can be shown that the marginal product of labor and capital is respectively
𝜕𝑥𝑖
𝜕𝑙𝑖 = 𝑓𝑎𝑖(𝑎𝑖)
𝜕𝑥𝑖
𝜕𝑘𝑖 = 𝑓𝑖(𝑎𝑖) − 𝑎𝑖𝑓𝑎𝑖(𝑎𝑖)
The firms maximize their revenue, Y, so that 𝑌(𝑃𝑖, 𝑘𝑖, 𝑙𝑖) = 𝑚𝑎𝑥{𝑃𝑖𝑥𝑖− 𝑤𝑙𝑖 − 𝑟𝑘𝑖}, where 𝑃𝑖 is the price of the good in each sector, 𝑤 the wage of labor and 𝑟 the returns to capital.
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The resulting first order conditions show that the return to each factor equals the value of its marginal product:
𝑤 = 𝑃𝑖𝑓𝑎𝑖(𝑎𝑖) , 𝑖 = 𝑝, 𝑜 (2)
𝑟 = 𝑃𝑖𝑓𝑖(𝑎𝑖) − 𝑤𝑎𝑖 , 𝑖 = 𝑝, 𝑜 (3)
From (2) we see that a firm’s choice of amount of labor per unit capital is a function of the relationship between the wage and the price of the firm’s product, or in other words, the real wage facing the firm. I call this function 𝑔𝑖, and write 𝑔𝑖(𝑃𝑤
𝑖) = 𝑘𝑙𝑖
𝑖. The function will have a negative first derivative, as the firm will demand less labor if the wage increases, but more labor if the price of the firm’s good increases. Multiplying both sides with 𝑘𝑖 also shows that the demand for labor is increasing in the amount of capital there is in the firm.
The consumer’s maximization problem is left in the background. The consumers are assumed to take prices as given and their relative demand is unaffected by income as they are also assumed to have identical homothetic preferences. Due to the latter, the consumers can be thought of as represented by one consumer.
For the factor market to clear we must have that:
𝑘𝑝+ 𝑘𝑜= 𝐾
𝑙𝑝+ 𝑙𝑜 = 𝐿
Where 𝐾and 𝐿is the country’s total endowment of capital and labor respectively.
Using (3), the sector-specific returns to capital can be written as
𝑟𝑖 = 𝑃𝑖𝑓𝑖(𝑎𝑖) − 𝑤𝑎𝑖 (4)
By differentiating (4) w.r.t. 𝑤 and 𝑃𝑖 we see that the return to capital goes down if the wage of labor goes up and that the return to capital goes up if the price of the firm’s good goes up, everything else being equal. The differentiations are performed keeping in mind that 𝑙𝑖 = 𝑘𝑖𝑔𝑖(𝑃𝑤
𝑖) and that 𝑥𝑘𝑖
𝑖 = 𝑓𝑖(𝑎𝑖):
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𝜕𝑟𝑖
𝜕𝑤 = −𝑎𝑖 + (𝑃𝑖𝑓𝑎𝑖 − 𝑤)𝑑𝑎𝑑𝑤𝑖= −𝑎𝑖 < 0 and
𝜕𝑟𝑖
𝜕𝑃𝑖= 𝑓𝑖(𝑎𝑖) = 𝑥𝑘𝑖> 0
In equilibrium, the returns to each production factor is equalized across the two sectors because of the assumption of long run, perfect mobility of production factors, so that:
𝑟𝑝(𝑃𝑝, 𝑤) = 𝑟𝑜(𝑃𝑜, 𝑤) (5)
The equilibrium can be shown graphically, as in figure 5, where the functions for returns to capital in the two sectors, 𝑟𝑝and 𝑟𝑜, intersect in point A.
Figure 5
The functions are downward sloping, showing that a higher return to capital will result in a lower wage for labor. The slope of the tangent to each curve in equilibrium is the factor intensity of each sector; the steeper the curve, the more intensive in labor is production.
3.2 The Stolper Samuelson theorem
The Stolper Samuelson theorem predicts that an increase in the price of a good will, in the long run, lead to an increase in the returns to the factor used intensively in the production of that good, and a decrease in the returns to the factor used intensively in the production of the other good. The percentage increase in the returns to the first factor will be larger than the increase in the price, because the original price increase is enhanced by a structural change, triggered by the increase in the price.
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In the Heckscher-Ohlin model framework, labor can at all times move freely between the two sectors. In the short run, capital is fixed in each sector, but in the long run, capital can also move between the two sectors. What will happen to the returns to the two factors of production in the short run will vary according to which factor is intensive in the production of the good that experiences a price increase. The effects that will prevail in the short run are the same in the Stolper Samuelson theorem as in the Ricardo Viner specific factor model7. I assume a so called diversified equilibrium, implying that the country is endowed with enough labor and capital for both goods to be produced. As in the rest of the thesis, I consider an increase in the price of oil when presenting the theorem. I will present both the case where the petroleum sector is intensive in capital and the case where the petroleum sector is intensive in labor.
When the petroleum sector is intensive in capital
I start out by assuming that the petroleum sector is intensive in capital and that the rest of the economy is intensive in labor. In order to explain the mechanisms of the structural change and the changes in factor prices in the short and long run, I make use of figure 6. In the right part of the figure, the wage and the returns to capital have switched places on the axes relative to figure 5, so now the slope of the curves represents the amount of capital per unit of labor. In the left part of the figure, the amount of labor in the petroleum sector is measured from the left to the right on the horizontal axis and the amount of labor in the rest of the economy is measured from the right to the left.
Figure 6
7 The Ricardo Viner model has three factors of production: capital that is specific to each sector and labor that can move freely between the sectors.
15 Initially, the economy is in equilibrium 𝐸, where the wage of labor is 𝑤 and the returns to capital is 𝑟. Then the price of petroleum increases and the country is induced to produce more petroleum. In the short run, this will lead to an increased demand for labor in the petroleum sector, which will give a shift of labor towards the petroleum sector and a higher wage. This is shown in the figure as a shift to the right in the petroleum sector’s demand curve for labor, 𝑤 = 𝑃𝑝𝑓𝑎𝑝(𝑎𝑝), from 𝐴𝐴 to 𝐴̂𝐴̂ and an increase in the wage of from 𝑤 to 𝑤̂. The price increase also leads to a shift to the right of the function for the return to capital in the petroleum sector, and in the short run the returns to capital in this sector increases to 𝑟̂𝑝 and the returns to capital in the rest of the economy decreases to 𝑟̂𝑜.
In the long run, the difference in returns to capital between the two sectors will lead to a shift of capital from the rest of the economy towards the petroleum sector. With more capital, the demand for labor in the petroleum sector will increase again. In the rest of the economy the need for labor becomes smaller with less capital, so the rest of the economy reduces their demand for labor, given by 𝑤 = 𝑃𝑜𝑓𝑎𝑜(𝑎𝑜). Since the rest of the economy is intensive in labor it uses more labor per unit of capital than the petroleum sector. The negative shift in the demand curve for labor for the rest of the economy will thus be larger than the positive shift in the demand curve for the petroleum sector. This leads to a reduction in the wage. The movement of capital and labor will continue until enough capital has been transferred to the petroleum sector and the wage has been reduced so much that the returns to capital is again the same in both sectors. At this point the petroleum sector’s demand curve for labor has shifted from 𝐴̂𝐴̂ to 𝐴̅𝐴̅, and the rest of the economy’s demand curve for labor has shifted from 𝐵𝐵 to 𝐵̅𝐵̅. The wage has been reduced from 𝑤̂ to 𝑤̅ and the return to capital is now 𝑟̅ in both sectors. The new long term equilibrium is in point 𝐸̅.
The structural change with the movement of both capital and labor to the petroleum sector has led the returns to capital to increase more than the increase in the price of petroleum. This can be seen in the figure as well. The distance between the petroleum sector’s return to capital curves, with the new and the old price, shows the price increase. This distance is clearly smaller that the distance between 𝑟 and 𝑟̅, which shows the increase in the return to capital.
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When the petroleum sector is intensive in labor
In the following I will look at the mechanisms predicted by the Stolper Samuelson theorem to follow from an increase in the price of petroleum under the assumption that the petroleum sector is intensive in labor, as opposed to capital. The rest of the economy is now assumed to be intensive in capital. I use figure 7 to explain the effects in the short and the long run of the increase in the price of petroleum. In this figure, the petroleum sector and the rest of the economy have switched places, relative to figure 6. In the left part of figure 7, the amount of labor in the petroleum sector is now measured from the right to the left on the horizontal axis and the amount of labor in the rest of the economy is measured from the left to the right. The slopes of the functions for returns to capital in the right part of the figure show that the petroleum sector is now intensive in labor.
Figure 7
The economy starts out in the equilibrium point 𝐸. In the short run, an increase in the price of oil will lead to increased demand for labor in the petroleum sector and increased wages. This is shown in the figure as a shift in the petroleum sector’s demand function for labor from 𝐴𝐴 to 𝐴̂𝐴̂ and an increase in wages from 𝑤 to 𝑤̂. There will also be a rightward shift in the petroleum sector’s returns to capital curve, and the returns to capital in the petroleum sector will increase from 𝑟 to 𝑟̂𝑝, while the returns to capital in the rest of the economy will fall from 𝑟 to 𝑟̂𝑜.
In the long run, the difference in the returns to capital in the two sectors will lead to a movement of capital towards the petroleum sector. With more capital, the petroleum sector will demand more labor and its demand curve for labor will shift even more to the left. The rest of the economy’s demand for labor will fall as capital is moved away from this sector,
17 and its demand curve for labor also shifts to the left. Because the petroleum sector is intensive in labor and uses more labor per unit of capital than the rest of the economy, the positive shift in the petroleum sector’s labor demand curve will be larger than the negative shift in the labor demand curve of the rest of the economy. This will drive up the wages even more. The movement of capital and labor will continue until enough capital has been moved, and the wage has increased so much that the returns to capital is again the same in both sectors. In the new equilibrium, 𝐸̅, the demand curves for labor of the petroleum sector and the rest of the economy have shifted from 𝐴̂𝐴̂ to 𝐴̅𝐴̅ and 𝐵𝐵 to 𝐵̅𝐵̅ respectively. The wage has increased even more relative to the increase in the short run, from 𝑤̂ to 𝑤̅ and the returns to capital have fallen to 𝑟̅.
In the case of a labor intensive petroleum sector the structural change following from the price increase of oil has led the wage to increase more than the increase in the price. This shown in the figure 7, by a smaller distance between the two returns to capital curves of the petroleum sector than the distance between 𝑤 and 𝑤̂.
The predictions of the Stolper Samuelson theorem in the short and in the long run
The above presentation of the Stolper Samuelson theorem has shown that the long run effects of a change in the price of a good on the factor used intensively in the production of that good is the same whether the intensive factor is labor or capital. Following a price increase, the returns to the factor used intensively in the production of that good will increase more than the price of the good increased. The opposite will happen in the case of a reduction in the price of a good.
In the short run, however, we get different predictions for the returns to the intensive factor of production, depending on whether the factor is labor or capital. If the price of a labor intensive good increases, the wage of labor will increase in both sectors of the economy in the short run. If however the price of a capital intensive good increases, the returns to the capital which is specific to the sector that experiences the price increase in the short run will increase, while the returns to the capital in the other sector will decrease. In the case of a decrease in the price of a good, the opposite will happen to the intensive factor in the short run.
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3.3 Discussion of assumptions
The Heckscher-Ohlin model and the Stolper Samuelson theorem are considered as highly important contributions to trade theory. The theories have however also been subject to criticism because of the simplified assumptions they are built on (Feenstra, 2004, p. 35). In this section I examine some of these assumptions.
Assuming two goods and two input factors in a country is a strong assumption which can be subject to critique. However, the Heckscher- Ohlin model still provides qualitatively important insights. It has also been shown that generalizing the model to a NXM one, with i = 1, … , N goods and j = 1, … , M input factors, and with N = M, a weaker version of the Stolper Samuelson theorem still holds (Feenstra, 2004).
The assumptions of complete factor mobility across industries within a country and with wages determined solely by world prices and technology parameters are also less likely to hold in a real world setting. As described in section 3.2, the Stolper Samuelson theorem assumes that one of the input factors can respond immediately to a price change, while the other factor will respond after some time. However, in the short run, it is likely that there will exist some frictions in the labor market limiting this free mobility of labor within a country, also in the short run. The framework assumes that all workers are the same, while in reality, differences in the characteristics of workers typically makes it challenging for a worker to move freely between industries.
One may also question the assumption of constant factor endowments. In the particular case analyzed in this thesis, the substantial increase in international labor migration that has taken place in the aftermath of the European Union Eastern enlargement in 2004 should be accounted for. Furthermore, as we have seen above, the Norwegian petroleum sector does not only employ workers residing within the country and there are also non-residential workers employed in Norwegian firms in this sector.
The strong and simplifying assumptions of the Stolper Samuelson theorem might contribute to reduce the predictive power of the theorem. However, even though the assumptions of the Heckscher- Ohlin model and the Stolper Samuelson theorem are highly simplified, the model can be used for achieving some insights in particular economic situations, which is what will be the tool for the analyses of this thesis.
19 3.4 Review of empirical literature on the Stolper Samuelson theorem
This section will present some empirical literature on the Heckscher- Ohlin framework and the Stolper Samuelson theorem. There is much empirical literature on the topic and the studies yields different results.
Leontief (1953) was the first to test the Heckscher-Ohlin framework (Feenstra, 2004). He measured the capital to labor ratio of the U.S. exports and the capital to labor ratio of the imports, by assuming that the technology in countries where the imports came from was the same as in the U.S. As the U.S. was assumed to be capital abundant, Leontief expected to find a higher capital to labor ratio for exports than for imports. However, his results showed the opposite, which contradicted what was predicted by the Heckscher-Ohlin model. This result was called the Leontief paradox. However, it was later criticized and found to have been performed wrongly (Feenstra, 2004). Instead of measuring the capital to labor ratio of the exports and imports, Leamer (1980) proposed that one should measure the capital to labor ratio of production and consumption. Doing this, he found that the capital to labor ratio was higher for production than for consumption in the U.S., which coincided with the notion that the U.S. was capital abundant and confirmed the predictions of the Heckscher-Ohlin model.
Later, much attention was given to the widening income gap between high and low educated workers in OECD countries like the U.S. and the U.K., as well as in Mexico, since the 1970s.
Researchers investigated whether this increasing income gap could be explained by the liberalization of trade. The studies usually focused on rising wage inequality between low- and high-skilled labor, although the real wage of many low-skilled workers, especially in the U.S., also decreased over the last 30 years of the 20th century (Slaughter, 2000). These studies were based on the notion that by opening up their markets and increasing the trade with low- skill abundant developing countries, prices on goods that were intensive in low-skilled labor would be reduced on the home market relatively to prices of goods that were intensive in high-skilled labor. Following from this, the relative wages of low-skilled labor would fall, which was what had been observed in e.g. the U.S.
Slaughter (2000) summarizes two main empirical approaches that have been used to test whether this could be the explanation for the widening income gap, by reviewing empirical studies of the U.S. in the period of concern. These are so called consistency checks and mandated wage regressions. The consistency checks investigate whether reduced barriers of
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trade led to reduced prices of goods that were in fact intensive in low-skilled labor in production relative to goods that were intensive in high-skilled labor. Lawrence & Slaughter (1993), Krueger (1997) and Sachs & Shatz (1994) are examples of authors who have performed such tests. Lawrence & Slaughter (1993) find that the price developments in the U.S. in the 1980s did not support the predictions of the Stolper Samuelson theorem. Krueger (1997) find evidence supporting the Stolper Samuelson theorem in the U.S. from 1989 to 1995 and Sachs & Shatz (1994) find evidence that supports the theorem in the 1980s in the U.S., by treating the computer sector separately from the other sectors due to large price decreases in this sector following from productivity increases.
Mandated wage regressions are regressions of zero-profit conditions of different industries expressed as changes. In these regressions the price of the products are the dependent variable. Factor-cost shares, measuring the factor intensities in production, are the independent variable and changes in factor prices are the parameter estimate. The resulting parameter estimate is a measure of a “best guess” of the changes in factor prices that should result from changes in goods prices, while maintaining the zero-profit condition of the Heckscher-Ohlin framework. By comparing the result with the actual change in relative wages, the researcher is able to find an estimate of how much of the actual changes in factor prices that resulted from a change in the relative product price (Slaughter, 2000).
Krueger (1997), Robertson (2004), Baldwin and Cain (1997) and Hanskel and Slaughter (2001) have performed various versions of such tests. Robertson (2004) finds evidence consistent with the Stolper Samuelson theorem in Mexico after the country entered the General Agreements on Tariffs and Trade (GATT) in 1986 and the North American Free Trade Agreement (NAFTA) in 1994. Baldwin and Cain (1997) conclude that Stolper Samuelson effects did not play any significant role in the increased wage inequality in the U.S. in the 1960s, 1970s and 1980s, while Hanskel and Slaughter (2001) find that changing prices were important contributors to raising inequality in the UK in the 1980s. Slaughter (2000) argues that the mandated wage regressions are better at testing the Stolper Samuelson theorem on rising wage inequality in this period than the consistency checks. The main argument is that the former is able to correct for other factors than changes in product prices that may affect the development of factor prices.
The main opposing argument against reduced trade barriers as the reason for increased wage inequality, in e.g. the U.S. and Mexico, in the second half of the 1900s is changes in
21 technology that might have reduced the need for low-skilled labor. This argument can be thought of as a factor other than product price changes that could have affected relative wages, but it could also be that changes in technology were, to some extent, passed through to factor prices (Slaughter, 2000). As the results of the studies investigating these two main opposing explanations for increased inequality varies a lot, there does not seem to be a clear conclusion on how strong the role of increased trade with developing countries was for the widening relative income gap in the U.S. and the U.K. in this period (Abrego & Edwards, 2002).
Slaughter (2000) also questions how fast one should expect factor prices to be able to adjust to changes in product prices as predicted by the Stolper Samuelson theorem. The theorem describes mechanisms that will prevail in the long run, but does not suggest what is actually meant by the long run. In his paper, Slaughter (2000) surveyes nine articles, some of which are listed above, that uses consistency checks and mandated wage regressions to investigate the increasing wage inequality in the U.S. However, all of these sudies lookes at changes in wage inequality and product prices that occurred over the same period. Slaughter arges that if there exists sufficiently large frictions in the labor market in the short run to make the adjustment period of the economy longer than the timehorizon considered in these studies, the conclusions from these might not be correct. Robertson (2004) takes this into account and lookes at the time frame of Stolper Samuelson effects in Mexico from 1987 to 1999 by using a band pass filter on time series. He finds that in this case, it took three to four years for the changes in relative wages to follow the changes in relative prices. Blanchard & Katz (1992) investigate the labor mobility between U.S. states after demand shocks that led to increased unemployment in some states and find that it can take up to five to seven years before people in one state decides to move to another state due to unemployment after such a shock.
While not directly adressing the Stolper Samuelson theorem, later research has focused on effects on labor markets in OECD countries of increased import competition from China, after the country’s entry ino the World Trade Organization in 2001. Balsvik, et al. (2015) investigate the effects on Norwegian regional labor markets and find that between 1996 and 2007, import competition from China can explain almost 10% of the reduction in the manufacturing employment’s share of total employment in Norway. They did not find evedence that the import competition from China caused any effects on wages. This was explained by the way the Norwegian labor market is structured. There is much flexibility for
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employers with respect to adjusting employment according to economic fluctuations facing firms, but centralized wage bargaining contributes to less flexibility on the wage margin.
Autor, et al. (2013) found even larger effects of increased imports from China on the reduction in the share of employment in manufacturing in the U.S. in the period of 1990 to 2007, as well as significant wage effects.
A review of the empirical literature shows that the empirical research on the Stolper Samuelson theorem has mainly focused on the effects of increased competition from international trade rather than on other sources of price shocks, such as the one studied in this thesis, namely the price of oil. While the studies of the 1990s and early 2000s focused on changes in wages predicted by the theorem, studies of the effects on increased competition from China in the later 2000s also focused on the structural change.
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4 The price of oil and structural change
In this chapter I assess the main focus of the thesis, namely the process of the structural change that is predicted by the Stolper Samuelson theorem to follow from a change in the price of a good. In the Heckscher- Ohlin model this structural change is shown as a movement of the two factors of production towards the one of the two sectors that experiences a relative price increase, and away from the sector that experiences a relative price decrease.
However, in a real world setting, addressing this structural change becomes more complicated, mainly for two reasons. First of all, there are more than two sectors in an economy. This means that if one were to arrange the sectors according to the intensity in the use of a production factor, one of the sectors would be the most intensive in the use of that production factor and another sector would be the least intensive in the use of that production factor. However, there would be a range of other sectors between these two, using the production factor with different intensities.
Second of all, the Heckscher- Ohlin model does not include intermediate or investment inputs as a factor of production. The Heckscher- Ohlin model thus ignores the flow of goods between the different sectors of an economy that are used as inputs in production. As seen in chapter 2.3, this flow of intermediate and investment inputs between the sectors gives rise to what can be referred to as direct and indirect employment effects, through direct and indirect deliveries to a sector.
In this chapter I will attempt to reveal Stolper Samuelson effects of a structural change in the Norwegian economy predicted to follow from changes in the price of oil by taking this limitation of the Heckscher- Ohlin model into account. I want to look at the developments of employment in the petroleum sector and the developments in the employment directly and indirectly attributable to the petroleum activities through deliveries to the petroleum sector, in light of the development of the oil price.
I address the period from 1992 to 2013. This period is suitable for studying effects predicted by the Stolper Samuelson theorem as it covers large movements in the price of oil, including three steep increases between 1998 and 2000, 2003 and 2008, and 2009 and 2012, as well as decreases after 1997, 2000, 2006 and 2008.
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4.1 The predictions of the Stolper Samuelson theorem
Chapter 3 presents the Stolper Samuelson theorem naming the two production factors of the model framework capital and labor, where capital is specific to each sector in the short run and where labor can move freely between the two sectors, in both the short and the long run.
The characteristics of these two production factors can also be attributed to different types of employment. Employment can be thought of as labor that can move freely between the sectors all the time, or as human capital that is specific to each sector in the short run. Human capital is thought of as knowledge that is unique for each sector. It is a fixed cost to the firm that cannot be scaled up or down with production in the short run.
When thinking about the employment as described above, the Stolper Samuelson theorem predicts that an increase in the price of oil will be followed by a movement of labor towards petroleum activities in the short run, and a movement of both labor and human capital towards petroleum activities in the long run. In the case of a decrease in the price of oil, the opposite is predicted to happen. According to the Stolper Samuelson theorem, I thus expect a movement of employment towards petroleum activities in the case of an increase in the price of oil, and a movement of employment away from petroleum activities in the case of a decrease in the price of oil, in both the short and the long run.
4.2 Data and method
Data on employment in the petroleum sector is collected from Statistics Norway’s annual national accounts (Statistics Norway, 2016a). However, as seen above, considering only the employment in the petroleum sector would underestimate the importance of the petroleum activities for the total employment in the Norwegian economy. I would not be able to follow the development in the employment that is attributable to petroleum activities through direct and indirect deliveries to the petroleum sector. In order to find the development of the employment directly and indirectly attributable to the petroleum activities, an analysis of Statistics Norway’s input-output tables for domestic production is performed, while also making use of employment data from the annual national accounts (Statistics Norway, 2015).
The input-output tables for domestic production contain information on how much in value all Norwegian industries deliver of intermediate inputs to each other, as well as the value of all that is produced by each industry. The firms described in section 2.3 are typically the most
25 important providers of direct deliveries, but the input-output tables show that most sectors of the economy have some direct deliveries of intermediate inputs to the petroleum sector. The tables do not contain information on deliveries and demand for investment goods and services, which as described earlier on, are also important inputs in the production of the petroleum industry. Later in the chapter I will come back to how I attempt to work around this.
As seen in chapter 2.3, indirect deliveries to the petroleum sector consist of a chain of sub- deliveries that can be traced far back, before the final good arrives at a firm in the petroleum sector. Ideally, I would follow this whole chain of sub deliveries. This is done by Eika et al.
(2010) and Midsem et al. (2015) by making use of an input-output model when calculating employment directly and indirectly connected to petroleum activities. However, because of lack of access to such a model, I choose to include the employment effects of two “rounds”
backwards in the chain of deliveries: employment connected to the direct deliveries and employment connected to the first round of indirect deliveries to the petroleum sector.
Blomgren et al. (2011) have calculated the effects on employment of petroleum activities in the Northern Sea in 2010 all the way back to the seventh round of the chain of deliveries.
They found that the effects were clearly strongest in the first two rounds, before dropping significantly after the second round. Assuming that the same is true when considering petroleum activities on the whole of the Norwegian continental shelf, looking at the first two rounds will capture a lot of the effects on employment. Estimations are done for the years 1992, 1996, 2000, 2004, 2008, 2010 and 2013, in order to get a good picture of how the employment attributable to petroleum activities has developed over the period studied.
The first step is to estimate employment generated in the first round. Using the input-output tables, I find the share of total production in each sector that is delivered as intermediate inputs to the petroleum sector. These shares are combined with data on employment in each sector in order to find an estimate on how many of the workers in each sector that can be attributed to the production of goods for the petroleum sector. The estimate is dependent on the assumption that the factor intensity in production of the goods in each sector is the same, independent of the types of goods or services produced, and who the goods or services are delivered to.
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Because the sector “building of oil platforms and modules” is an important supplier of investment goods, this sector is left out of the estimation of workers attributable to the production of intermediate inputs to the petroleum sector8. Instead, the total number of employees in this sector is added to the total number of workers attributable to the petroleum sector later on. This can be done because the sector produces solely for the petroleum sector.
However, data for employment in this sector alone is not available, but found together with the number of employees in the sector “building of ships” in the national accounts. This might lead to an overstatement of workers attributable to petroleum activities. However, considering that other sectors than the sector “building of oil platforms and modules” deliver investment goods to the petroleum sector as well, the overstatement of workers in the former might compensate somewhat for the latter. However, it is likely that the analysis will not capture the full amount of workers attributable to the production of investment goods that are delivered to the petroleum sector. In order to avoid double counting, it is necessary to exclude the deliveries the petroleum sector makes to itself form the calculations.
When estimating the number of workers that can be attributed to the second round, the first step is to find the share of total production in all sectors that is delivered to all other sectors.
Like in the estimations of the first round, the petroleum sector and “building of oil platforms and modules” are left out of the calculations, and deliveries that all sectors have to themselves are netted out. From there, employment data are used to calculate the number of workers that can be attributed to deliveries to all sectors from all sectors. The next step is to combine these numbers with the share of total production in each sector that is delivered to the petroleum sector. The result is an estimate of how many workers in each sector that can be attributed to deliveries to the petroleum sector through deliveries to other sectors that produce intermediate products to the petroleum sector.
In addition to estimating the numbers of workers in round one and two, the percentage of total employment in Norway that is attributable to the petroleum activities through these rounds is found. This is done in order to investigate whether the same trends still hold when taking the
8 In the input-output tables, “building of oil platforms and modules” are included in the category “other transport equipment” together with the production of ships, railway locomotives, aircraft machinery, military fighting machinery, motorcycles and bicycles. Except for ships, these are not typical goods needed in petroleum activities, so therefore I choose to leave out the whole category.