There exists a substantial body of literature concerned with the calibration of the Heston model for pricing financial derivatives under stochastic volatility, many of which rely on computationally expensive algorithms. Our paper evaluates a calibration method of the Heston model proposed by Alòs, De Santiago, and Vives (2015), which can be used to price derivatives with little computational effort. The calibration method is innovative in the sense that it considers only the three most critical regions of the implied volatility surface. The regions where the underlying option is, firstly, at-the-money, secondly, close to maturity and lastly, far away from maturity. Although their procedure is parsimonious and very easy to implement, they calibrate a model whose empirical applicability is contested.
The main contribution of our paper is the evaluation of their model in an extensive numerical exercise as well as an application to real data. Collecting empirical option data has been one of the main challenges with respect to this work, since historical data on financial derivatives is not accessible to the public. Faced with this issue we have written a script that allowed us to automatically scrape option data at a high frequency over just a couple of weeks. Thus, we build our own extensive data base. Also, we have made the data and code available on https://griipen.shinyapps.io/bgse/ and https://github.com/HitKnit/BGSE2018/tree/HitKnit-optionscraping, respectively.
In terms of our results, we find that whilst the calibration method has solid theoretical foundations and produces satisfactory estimation results within the theoretical Heston universe. However, it fails in practice. Specifically, for the numerical exercise we find that out of all simulations the maximum average error across the entire volatility surface is 0.999 percent while the mean error across simulations is only 0.481 percent. In sharp contrast to that, absolute percentage errors for our empirical data are on the order of 30-40 percent in many cases. In the following figure, we present our findings for intra-daily data from May 16, 2018. The left column shows empirical implied volatilities for a European call option on Facebook Inc. (FB) stocks. From top to bottom volatilities are shown for the opening, lunch and closing sessions. The central column shows the fitted volatility surfaces while the right column shows absolute percentage differences between empirical and estimated values. The finding that errors are particularly high for at-the-money options with short times to maturity is robust across the entire data sample.
Conclusions and key results:
In light of these results, we conclude that inherent limitations of the Heston Model disqualify the calibration for practical use. Nonetheless, we believe that similarly simple calibration methods as the one examined here should be used in combination with more sophisticated option pricing models.
Our paper analyzes the impact of a cash transfer program targeting households in extreme poverty in Uruguay, called the Tarjeta Uruguay Social (henceforth referred to as TUS). In the past decades, cash transfers have become one of the main social assistance policies used to address poverty and inequality in developing countries. Their objective is to reduce vulnerability by increasing and smoothing household income, although additional objectives are usually defined depending on the program and country, such as increasing access to health and education, and reducing food insecurity (DFID 2011; Honorati et al. 2015).
The impact of these programs on different life outcomes has been widely studied. Overall, positive impacts on poverty, food insecurity, child school enrollment, labor outcomes, health and social cohesion have been found (DFID 2011; ODI 2016). Nevertheless, more research is still needed to understand the channels and particular aspects that determine their success, since countries differ widely in the details of program design. In our research, by taking advantage of considerable design modifications since the implementation of TUS, we evaluate the impact of the amount of the transfer and the benefit duration on relevant outcomes.
The Tarjeta Uruguay Social (TUS) is a conditional cash transfer program implemented in 2009 which aims at assisting those in situations of extreme poverty in Uruguay. It targets the 60,000 worst-off households by providing them with a monthly cash transfer on a prepaid magnetic card. This card can be used to purchase food items, cleaning supplies, and hygiene products, excluding cigarettes and alcohol. Eligibility for the program is based on the Critical Needs Index (CNI), a proxy means test that evaluates household poverty, using variables associated to education, dwelling, access to durable goods and household composition. The program has undergone many modifications since its inception, including increasing the number of participants, changing the eligibility criteria, and a doubling of the benefit for half of the recipients. Our analysis begins in 2013, in which the program had 60,000 participants, and the poorest 30,000 according to the CNI received a doubling of their benefit, creating two benefit categories: Simple TUS and Double TUS. In our research, we exploit the doubling of the benefit based on the CNI by using a Fuzzy Regression Discontinuity Design to evaluate the impact of the amount of the benefit on life outcomes.
The availability of an extensive set of administrative data allowed us to evaluate the impact of the doubling on an array of outcomes. There are many different channels through which this cash transfer program could have positive effects, since the resources freed up by the relaxation of the household budget constraint could be used differently according to household preferences. Therefore, by taking advantage of a rich set of administrative data, we analyzed 65 outcomes: housing and living conditions, food insecurity, formal labor market work, education enrollment of children and adolescents, prenatal and birth health conditions, and family composition. Additionally, we analyze how the duration of the benefit affects the impact of the program by comparing the effects for beneficiaries who receive the transfer for different time periods. We analyze short-term outcomes for those who receive the transfer for less than a year; medium-term outcomes for those who receive the transfer for two to three years; and long-term outcomes for those who receive the transfer consistently for three years.
Our results show than an increase in the amount of a cash transfer can in fact have important impacts on the life outcomes of recipients. Positive effects were found with regard to living conditions, with an increase in investment in durable goods and a betterment of housing conditions, such as purchasing water heaters or washing machines, adding a bathroom to the home, and upgrading from a trash roof to a concrete one. Additionally, results show positive impacts concerning individual outcomes, with improvements regarding prenatal care and months of formal work observed. Nevertheless, some negative results were found in the short-term, which could potentially be explained by an attempt of manipulation by the beneficiaries in order to ensure continued benefit provision under uncertainty. Results also show that the duration of the benefit has a considerable impact on how the transfer is spent. More positive significant household results are found in the medium-term, while individual results become stronger in the long-term. The increasing effects of more persistent benefits could potentially be explained due to uncertainty in the short-term regarding whether the benefit will continue to be provided, which decreases over time.
This study contributes to the literature of poverty alleviation policies by providing evidence which can be used to improve the design of cash transfer programs. The positive effects found in this paper from comparing different amounts of the transfer within the same program indicate that the monetary amount of the benefit is a relevant policy parameter with consequences for the effectiveness of the program. Additionally, the results for heterogeneous effects by benefit duration indicate that the persistence of the transfer is another relevant aspect of program design. The evidence provided in this paper indicates that a predefined duration upon entering the program together with a minimum duration of one year could constitute a good practice. This may mitigate negative effects regarding household manipulation attempts and potentiate positive effects by reducing income volatility and increasing housing investments. Our results suggest that further research on benefit size and timing is imperative for policy design of cash transfers, one of the main tools to reach universal social protection.
The goal of this paper is to assess quantitatively the impact that the emergence of China in the international markets during the 1990s had on the U.S. economy (i.e. the so-called China Shock). To do so, I build a model with two sectors producing two final goods, each of them using as the only input of production an intermediate good specific to each sector. Final goods are produced in a perfectly competitive environment. The intermediate goods are produced in a frictional environment with labor as the only input. First I calibrate the close economy model to match some salient stylized facts from the 1980s in the U.S. Then to assess the China Shock I introduce a new country (China) in the international scene. I proceed with two calibration strategies: (i) calibrate China such that it matches the variation in the price of imports relative to the price of exports for the U.S. between the average of the 1980s and the average of 2005-2007, (ii) Calibrate China such that variation in allocations are close to the ones observed in data, for the same window of time. I found that under calibration (i) the China Shock in the model explains 26.38% of the variation in the share of employment in the manufacturing sector, 16.28% of the variation in the share of manufacturing production and 27.40% of the variation in the share of wages of the manufacturing sector. Finally, under calibration (ii) I found that the change in relative price needed to match between 80 to 90 percent of the variation in allocations is around 3.47 times the one observed in data.
Conclusions and key results:
According to the model, the China Shock explains 26.35% of the variation in the share of manufacture employment, 16.28% of the variation in the share of manufacturing production and 27.44% of the variation in the share of wages of the manufacturing sector. The first of these results is consistent with findings in Autor et al. (2013). On the other hand, the variation in the unemployment rate of the economy is not matched, neither for the first nor the second calibration of the open economy. I also found that as a consequence of the China Shock, real wages increase when measuring them in terms of the price of the import good, and decrease when measured in terms of the price of the export good. This result is not in line with findings in Autor et al. (2013). The optimal unemployment insurance in the open economy is 6.13% of average wages higher than in the close economy because the unemployment rate of the open economy is higher than in the close economy (0.9% difference). Finally, the model generates a non-traditional source of comparative advantage, arising from differences in the relative bargaining power of workers.
We capitalise on the 2006 implementation of a minimum wage for the hospitality sector to make well-evidenced inferences about the impact of the upcoming National Minimum Wage (NMW) Legislation on low-wage workers. Our paper focuses on the two largest low-wage sectors currently without minimum wage regulation, which are manufacturing and construction. Two regression specifications and sensitivity analysis are used to provide insights into the implication for wages, hours worked, employment, formality and poverty rates. In light of our results and a comprehensive review of the literature, we conclude that the NMW will be largely beneficial for low-wage labourers. Our critical recommendation for policymakers is the need for complementary policies to ensure compliance and facilitate the transition of vulnerable groups (particularly black women) into the formal sector.
Conclusions and key results:
From our first specification, our analysis suggests that wages and hours worked will increase in manufacturing and construction sectors as a result of the minimum wage, mostly driven by increases for black and female workers. Although the policy is likely to increase the formality rate among male workers, we predict formality will fall among females as employers try to circumvent the legislation. Therefore it is crucial that adequate complementary policies are implemented to ensure the benefits are captured by all population groups. Our second specification exploits the variation in the median wage across provinces. In doing so, we find no significant effect on wages, which signals regional impacts of the minimum wage are fairly homogeneous. Therefore, compared to other countries adopting a similar policy, the implementation of safety-nets combating the adverse effects of the minimum wage will be relatively more straightforward. By conducting sensitivity analysis around compliance rates and poverty lines already stipulated in the literature, we predict between 100,000 and 300,000 manufacturing and construction workers will be lifted out of wage poverty as a result of the minimum wage. We combine our empirical partial equilibrium analysis with theoretical general equilibrium forces to provide statements on the anticipated lower bound of wage changes.
In this paper we study the dynamics and drivers of 10 year’s sovereign bond yields using a panel of the original 11 Eurozone countries (excluding Luxembourg). The interest of this study relies on the fact that despite very different macroeconomic policy stances in the variables that we believe determine interest rates among these countries, 10 years Eurozone bond yields almost perfectly converged during the 2000’s, before they suffered a sudden disconnection in the aftermath of the Great Financial Crisis.
To this end, we apply two different methodologies. A Panel Data approach (that we end discarding) and a Time Varying Coefficients model using the Kalman Filter, which allows us for capturing changes in the pricing mechanism of bond yields over time. Initially, by using the latter methodology without controlling for the volatility of the interest rates (which dramatically increased after 2008), we obtain very noisy results that are barely explainable, since the coefficients seem to be capturing these changes in volatility. Once we introduce in the filter a GARCH process for the variance-covariance matrix of the interest rates that we use in the Time Varying Coefficients approach, we manage to obtain much more meaningful and explicative results.
One of our key contributions is the inclusion of new fiscal and macroeconomic variables as determinants of yields in the different Eurozone countries, which were discarded by other studies in the field. We also contribute by controlling by common determinants to all the Eurozone countries, which we obtained by applying a common component approach. Furthermore, our findings confirm that after the period of divergence in interest rates, started in the aftermath of the Great Financial Crisis, and caused by a refocus on fundamentals, Eurozone interest rates have converged again under the effect of a normalization of bond yield drivers, similarly to their pre-crisis levels, although not to the same extent. Another implication that we find is that in times of economic uncertainty and financial hysteresis, when default risk becomes an issue, the effects of government policy on interest rates can significantly lead to accentuated crowding out effects.
Conclusions and key results:
Our work indicates that there has been a significant break in the way sovereign debt was priced after the Great Financial Crisis of 2008, indicating a return to fundamentals as main drivers of sovereign yields. We find that several factors reflective of fiscal and macroeconomic stances became increasingly important during the crisis, after having been ignored in previous years. As such, Debt to GDP, Deficit to GDP, GDP growth and Current Account balances to GDP, among others, started to play important roles in the determination of long term interest rates for Eurozone government bonds. In line with previous research, our findings confirm the existence of 3 distinct phases in the euro bond market. A period of high integration, a period of disintegration, and a phase of partial reintegration (Adam and Lo Duca (2017)).
Our findings suggest that during periods of economic uncertainty characterized by high volatility in the financial markets, investors tend to focus on fundamentals, while in times of economic boom they do not discriminate too much among the different stance of these macroeconomic determinants. This finding has important policy implications since it suggests that during economic crises interest rates react much more to unsustainable fiscal policies and macroeconomic imbalances than during calmer times, causing a great private sector crowding out effect (Laubach (2011)).
Therefore, our results suggest that governments should pay closer attention to their fiscal stances during times of economic turbulence in order to avoid the detrimental effects of high interest rates on activity in a period of economic agent´s lack of confidence. As argued before by De Grauwe and Ji (2013), this former effect is exacerbated by the fact that Eurozone governments have no control over monetary policy, making impossible for them to reduce interest rates by no other means than sound fiscal policies. In line with this result, we notice that the ECB’s unconventional monetary policy (we obtain that the impact of short term interest rates -one of our common determinants obtained by principal components- on long yields has diminished over time) helped to bring down European bond yields after 2014. This fact contributed to put the fiscal stances of these countries, and other essential macroeconomic variables, back to sustainable levels, that along with the structural reforms carried out (which in addition to the former effect, have also contributed to bring back economic confidence and dynamism) have had by its own another loosening impact in the interest rates that these countries have been facing in every debt issuance.
Regarding the methodologies used to address our research question, we were able to obtain robust results and determine which method was the most appropriate to investigate the drivers of 10 year’s sovereign bond yields. We found that panel data approaches, which are widely used in the literature, lead to unstable and unsatisfactory results, causing us to attach limited credibility to the outcomes of such analysis. However, the Time Varying Coefficients approach seems more reliable and yields more robust and plausible results after we model the changes in volatility appropriately. We believe that having a larger sample (we use the forecasts released twice a year by the IMF in its World Economic Outlook and by the OECD in their Economic Outlook in order to control by the effect of the market´s forward looking in current levels of interest rates, as well as by reverse causality) would have allowed us to obtain more reliable results on this approach as well.
A suggestion for further research would be to apply Bayesian techniques to estimate our model. Indeed, given the limited amount of data available and the complexity of our models, these methods seem to suit better in this kind of estimation, where the great amount of parameters, as well as the possible presence of non-linearities, can make the optimization process very costly. Consequently, this methodology would have allowed us to also model the variance of the Time Varying Parameters, and not only the ones of the interest rates (our observables) with another GARCH or stochastic volatility process, since we expect that these variances could also follow a conditional process, which might have an impact on our estimation results.
Under the context of digital platforms who act as an intermediary between consumers and sellers, Price Parity Clauses (PPCs) is a contractual restriction for the seller not to sell at a lower price through any other channel (the so-called wide PPCs), or only in its own channel (narrow PPCs). These clauses present a trade-off between efficiencies and anticompetitive effects. On one side, PPCs act as a committing device of the seller to solve the show-rooming effect suffered by platforms (a particular form of free- riding), at the same time that it ensures platforms viability and enhances its incentives to invest and innovate. On the other side, PPCs allow platforms to charge higher fees, and lead to foreclosure of the market. Currently, neither the EC nor NCAs have set a clear guidance on how to assess these clauses. The main contribution of this paper is to set a legal standard for both wide and narrow PPCs using the cost-error analysis. The conclusions we arrived to are that wide PPCs should be per se illegal; and narrow PPCs should be presumed legal unless proven otherwise, except if narrow PPCs are eliminating the competitive restraints of the platform, in which case the standard should be that of rebuttable presumption of illegality.
Digital Economy will rise the use of Digital Platforms. Network externalities inherent to two-sided markets lead to high market power that make platforms an indispensable ally.
Digital Platforms use PPCs and this is capturing the interest of Competition Authorities. But there is no consensus with respect to the legal standard.
PPCs present a trade-off: On the one hand efficiencies results in reduction of search costs, prevents showrooming, incentives on investment and innovation. On the other hand, anti-competitive effects arise, creating high fees, foreclosure, collusion.
The results of our cost-error analysis are that Wide PPCs Min Type II error, therefore should be Per se illegal. Narrow PPCs Min Type I error: Rebuttable Presumption of Legality, except if (i) One-Stop Shop/Network; (ii) Brand Positioning; (iii) Switching costs: Min. Type II: Rebuttable Presumption of illegality
We identify contemporaneous and Granger-causal linkages between the 86 biggest companies, representing both the financial and real sectors, of the Eurozone economy that serve as paths of shock transmission. Network analysis lends itself very naturally to the study of systemic risk due to its preoccupation with interconnections and notions of centrality. We employ an estimation methodology introduced by Barigozzi and Brownlees (2018) using market data for daily volatilities from the Eurostoxx index. Our results are in line with the existing literature – the banking sector is found to be highly interconnected and responsible for most Granger-network spillovers. Moreover, only a small subset of firms appear to Granger-cause other residual volatilities, providing support for regulators’ targeting of Systemically Important Financial Institutions.
Following the work of Barigozzi and Brownlees (2018), this paper applies the nets algorithm to study the interconnectedness of the 86 biggest firms in the Eurozone for a sample period spanning from May 2008 to April 2018. We have estimated two sparse networks of return volatilities that allow us to measure systemic risk and detect patterns of its transmission. Compared to the original study of the US economy, we have utilised a more detailed set of industries. What is more, country-specific volatilities were added as an extra factor in order to obtain more precise firm-specific residual volatilities, while still uncovering a large number of connections.
At the contemporaneous level almost all industries exhibit high connectedness, a pattern which became immediately apparent on the initial heatmaps of residual correlations. Even when controlling for sectoral and country volatilities we find clusters of firms reacting strongly with other firms within the same business area. These co-movements are especially remarkable within the banking, industrial, and technological sectors.
However, it is a small subset of companies, mostly financial firms, that displays high interconnectedness at the Granger-causal level. Consequently, we conclude that banks are particularly important risk transmitters in the Eurozone network. The subset of banks is especially susceptible to volatilities stemming from other sectors. This makes intuitive sense as we can think of banks being highly leveraged when compared with other entities (Freixas et al., 2015). Moreover, banks amplify and transmit shocks to all the other sectors, which reflects their unique economic role as financial intermediaries. Altogether, this provides empirical support for the regulatory targeting of certain Systemically Important Financial Institutions.
This paper analyzes whether access to imported intermediate goods can raise export performance of Russian firms. We employ an instrumental variable strategy which exploits variation in firm-specific input tariffs to identify the effect of imported intermediates on firm exports during the period 2007-2013, utilizing a unique firm-level database on firm characteristics and customs declarations. We find that input tariff reductions can raise firm exports significantly, as can other measures aimed at increasing imports of intermediate goods of exporting firms in Russia. Import promotion targeted at exporting firms in high-tech sectors can be up to three times more effective. Better access to imports can also help increase the currently low share of exporting firms within the Russian enterprise landscape. Our results suggest that with the rising globalization and fragmentation of production processes, countries interested in raising exports need to think strategically of promoting imports as well. We propose and discuss several policy measures for Russia in the areas of tariff regulation, non- tariff measures, trade facilitation and trade integration.
Using a comprehensive firm-level dataset which combines information on Russian company characteristics, involvement in trade and input tariff rates, we reveal a strong positive impact of intermediate imports on firm exports in the manufacturing sector. These results imply that improved access to intermediate goods at the international market can serve as a means to raise Russia’s currently weak export performance outside the natural resource sector. Import promotion policies targeted at intermediate goods imported by firms in high-tech sectors can be especially effective and raise exports by up to three times more than in other sectors. Better access to imports can also help increase the currently low share of exporting firms within the Russian enterprise landscape.
Our estimation results indicate that a one percentage point decrease in input tariffs would raise firm exports by approximately one percent. Even though tariffs have been significantly decreased over the past decade in the context of regional integration and Russia’s WTO accession (see figure 1), there is still ample room to lower input tariffs in order to promote exports. More than 40 percent of intermediate goods imported by Russian exporting manufacturing firms and more than 30 percent of goods imported by exporting firms in high-tech manufacturing sectors still entered the customs union at a tariff rate above 5 percent in 2015. Besides tariff reductions, Russia could consider lowering non-tariff measures (NTMs) and enhancing trade facilitation, which can also contribute to better access to intermediate goods of exporting firms, as suggested by our IV results. As can be seen from figure 2, NTMs have increased sharply since Russia joined the WTO in 2012. It should be pointed out, however, that trade policies aimed at promoting imports of intermediate goods alone will not be sufficient to boost non-oil export growth and export competitiveness of Russian firms. To bring the desired success, they need to be combined with a range of other important policies, including improving access of Russian exporters to foreign markets and simplifying the existing export regulation, as well as comprehensive structural reforms and measures to improve the business environment.
Economics master project by Marc de la Barrera, Juraj Falath, Dorian Henricot and Jean-Alexandre Vaglio (Class of 2017)
Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2017. The project is a required component of every master program.
Marc de la Barrera, Juraj Falath, Dorian Henricot and Jean-Alexandre Vaglio
Our paper empirically investigates the impact of forward guidance announcements on inflation expectations in the Eurozone. The ECB first resorted to forward guidance on July 4, 2013 thereby expanding its array of unconventional policy instruments in the vicinity of the zero-lower bound. We use an ARCH model and identify forward guidance shocks as changes in the 2-year nominal ECB yield on specific announcement days to measure changes in daily inflation swaps of different maturities. In the process, we also separately identify the effect of quantitative easing and interest rate change announcement shocks. We find that forward guidance was successful in reviving inflation expectations in the medium to long term. Analyzing the transmission channels of forward guidance, we find evidence that both a reanchoring channel and a portfolio effect might have been at play.
Forward guidance shocks have a strong impact on inflation expectations with a one point decrease in 2-year nominal ECB yields pushing inflation expectations 37bps upwards five years ahead with high significance. Normalizing, a negative shock of one standard deviation in ECB yields had a 11bps positive impact. In Campbell’s terminology (Campbell et al. (2012)), market participants’ interpretation was Odyssean. Thereby, we broadly match the results found by Hubert & Labondance (2016) for the Eurozone. Since the impact persists at all horizons, albeit with decreasing amplitude, we suggest that a reanchoring channel à la Andrade et al. (2015) explains the bulk of the transmission. ECB forward guidance announcements have thus been effective in reducing the growing gap between agents’ beliefs in future monetary policy and ECB’s targets. Our results are also consistent with a portfolio effect à la Hanson & Stein (2015). We also document that QE announcements were more effective in amplitude than forward guidance announcements, probably through a reduction in the term premium.
In contrast, studies run by Nakamura & Steinsson (2013) or Campbell et al. (2012) suggested a larger Delphic channel was at play in the US. More precisely however, they found that their results were lower than those predicted by a New Keynesian model with sticky prices. Thus, a natural extension of this paper would be to explore how our results would compare to the predictions of a New Keynesian model. Another approach would be to build a counter-factual for inflation expectations in the absence of forward guidance. In any case, given that the ECB implemented forward guidance at a time of heightened uncertainty and while long-term inflation expectations were dropping, there are reasons to believe it could have been more efficient in the Eurozone than in the US.
On the theoretical side, it is important to understand the transmission mechanisms of forward guidance within a structural model. This would allow to understand the potential gap to empirical outcomes. A number of authors have already striven to embed forward guidance within New Keynesian models and it is still an active area of research. The objective is then to derive an optimal policy function for further times of monetary policy management under the ZLB constraint.
To complete the policy recommendation, one needs to weigh out the benefits of forward guidance against its undesirable side-effects. Poloz (2014) suggested that successful forward guidance could results in increased future volatility when restoring conventional communication. Campbell et al. (2012) highlighted that central bank commitment could have a cost in terms of inflation or credibility. It would then be interesting to assess the negative externalities of forward guidance.
Andrade, P., Breckenfelder, J., De Fiore, F., Karadi, P. & Tristani, O. (2015), ‘The ECB’s asset purchase programme: an early assessment’, ECB Working Paper (1956).
Campbell, J., Evans, C., Fisher, J. & Justiniano, A. (2012), ‘Macroeconomic Effects of Federal Reserve Forward Guidance’, Brookings Papers on Economic Activity 43(1), 1–80.
Hanson, S. & Stein, J. (2015), ‘Monetary policy and long-term real rates’, Journal of Financial Economics 115(3), 429–448.
Hubert, P. & Labondance, F. (2016), ‘The effect of ECB Forward Guidance on Policy Expectations’, Sciences Po publications (30).
Nakamura, E. & Steinsson, J. (2013), ‘High frequency identification of monetary non-neutrality: The information effect’, NBER Working Paper (w19260).
Poloz, S. (2014), ‘Integrating uncertainty and monetary policy-making: A practitioner’s perspective’, Bank of Canada Discussion Paper (2014-6).
Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2017. The project is a required component of every master program.
Alfredo Andonie, Andrea Greppi, Ece Yagman, Lorenzo Pisati and Moritz Degler
We investigate the effects of intellectual property products capital in the evolution of the labor share for five European countries. Using post-revision national accounts data, we construct a benchmark labor share with the contribution of both, traditional and IPP capital, against which we measure a counterfactual LS which isolates the effects of IPP. We report that the labor share in Austria, France, Germany, and Spain has been consistently declining, with high variation across countries. Our results show that part of this decline is explained by the inclusion and growing importance of IPP capital in the economy. A closer look at France reveals that the main channels through which IPP has an impact on the labor share are a higher depreciation rate and investment flow relative to traditional capital.
Our analysis of IPP capital and its impact on the LS reveals three main findings. First, we observe a decline in the LS of Austria, France, Germany and Spain, part of which is explained by the impact of IPP capital on aggregate income. Second, a cross-country comparison discloses great variation in both the magnitude at which the LS is falling in these countries and the extent up to which IPP capital can account for such a decline. Finally, a deeper analysis for France, in which we study the dynamics and composition of its aggregate capital, allows us to identify the higher depreciation rate and investment flow of IPP capital as the main channels driving the change in the trend of the LS.
We conclude that, to an extent, the behavior of the LS attests to the transition into more IPP capital-intensive economies. Since the inclusion of intangible capital in the revised European national accounts (ESA 2010), the growing importance of IPP relative to traditional capital has altered essential properties of aggregate capital, such as the depreciation rate. In particular, these changes have translated into new dynamics and ways in which factors are allocated in the economy.
In using revised data, our analysis presents novel evidence for LS dynamics in Europe and its relation with the composition of capital in the economy. From a measurement point of view, it highlights the way in which we have begun to think differently of developments and aggregate indicators. From a theoretical point of view, it compels us to reformulate models that can accommodate these new measurements and their implications for the rest of the economy.
As a final remark, we have not attempted to establish a connection between the LS and inequality. However, the relation between the compensation to labor and the concentration of IPP capital poses interesting challenges for future research. Particularly relevant to this study are the potential ways in which a decline in the LS propelled by an increase in IPP capital maps onto the evolution of inequality.
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