Evaluación Económica de Políticas Públicas: buscando atajos razonables

Javier Campos 25-09-2023 

Por Ginés de Rus, Javier Campos, M. Pilar Socorro y Jorge Valido

Una de las funciones del economista que genera una mayor rentabilidad social es ayudar en la selección de políticas públicas. Su contribución – la evaluación económica de las mismas – consiste en estimar el efecto neto sobre el bienestar social de la intervención examinada antes de que esta sea aprobada, ya sea una nueva regulación medioambiental, inversiones en infraestructuras, o un programa educativo o sanitario. La tarea no es fácil, pero renunciar a ella por su dificultad, o sustituirla por sucedáneos como los estudios de impacto, aumenta la discrecionalidad del político en las decisiones de asignación del gasto público y en la elección de cualquier otra intervención que modifique variables esenciales que acaban afectando al bienestar social.

La evaluación económica ex ante o, en otras palabras, el análisis coste-beneficio (ACB) es, en su acepción más genérica, la plasmación de la manera de pensar del economista o, definido como herramienta, la comparación cuantitativa de beneficios y costes sociales de una política comparada con contrafactual. El ACB es la metodología utilizada por los gobiernos de los países más avanzados y agencias supranacionales. Hay manuales de evaluación disponibles (véanse por ejemplo los del BEI, el ADB o la Comisión Europea) que contienen reglas sencillas de medición a partir de cantidades, precios y costes iniciales. También nos proporcionan valores de referencia para los parámetros más utilizados (por ejemplo, el valor del tiempo o el de una vida estadística) y algunas elasticidades (procedentes de estudios econométricos previos) que permiten proyectar los efectos de los cambios en las variables afectadas por la intervención.

Es evidente que los costes y beneficios de algunas actividades son más sencillos de valorar que los de otras; en el caso de las infraestructuras y servicios de transporte, por ejemplo, el ACB se ha desarrollado de manera extraordinaria, generándose un sólido cuerpo teórico y empírico que permite evaluar con cierta garantía una gran cantidad y variedad de proyectos y políticas (aquí).

En diferentes posts anteriores (véase aquí, aquí, aquí, o aquí, entre otros) hemos tenido la ocasión de discutir tanto las ventajas como las limitaciones del ACB, resaltando la necesidad de plantearlo en permanente búsqueda de un compromiso entre reglas sencillas (es decir, fáciles de aplicar y de explicar a los políticos y a la sociedad en su conjunto) pero que al mismo tiempo estén respaldadas por fundamentos teóricos que justifiquen los atajos que se toman para la medición. Dichos fundamentos teóricos minimizan los riesgos de obtener resultados espurios, provocados por dobles contabilizaciones, o por incluir o ignorar efectos en otros mercados afectados por distorsiones significativas.

En esta entrada queremos subrayar la importancia de partir de un marco analítico que permita utilizar dichos atajos razonables en la comparación con otras intervenciones que compiten por la utilización de fondos públicos. En este sentido, hay que insistir en que la evaluación económica de políticas públicas no debe confundirse con los estudios de impacto, como pueden ser la medición de efectos sobre el valor añadido bruto, el empleo, o el efecto multiplicador en la economía. Este no es el objetivo del ACB. Con el ACB buscamos el efecto neto en el bienestar social de una intervención que tendrá efectos en la utilidad de un conjunto amplio de individuos, heterogéneos en preferencias, en renta, afectados a lo largo de diferentes momentos en el tiempo y sometidos a shocks estocásticos que modifican la utilidad obtenida por cada individuo, y en cada periodo, de manera diferente. Un reto nada trivial porque hay que realizarlo situados en el presente, respetando las preferencias individuales y, entre otros retos, valorando bienes para los que no hay mercado. Todo esto sujeto a la disponibilidad de datos.

En un libro reciente, fruto del trabajo metodológico realizado por los autores de este post para la AIReF, con la colaboración de FEDEA e IVIE, y financiación de la Comisión Europea,[1] tomamos como punto de partida un sencillo modelo del que se extraen los criterios y reglas de medición de los beneficios y costes de intervenciones en los mercados de transporte. Posteriormente, aplicamos esta metodología a la evaluación de inversiones ferroviarias (aquí) y a una política de subvenciones al transporte aéreo (aquí y aquí). También analizamos la relación entre la fijación de precios y la inversión en el contexto de la evaluación económica (aquí), y en sus consecuencias para la configuración de equilibrios irreversibles a largo plazo que no serían óptimos con otros sistemas de tarificación.

La idea central que motiva esta entrada es insistir en que la base teórica del ACB no es otra que el equilibrio general y la economía del bienestar, además de la utilización concienzuda de técnicas econométricas. A veces se contrapone, erróneamente, el ACB con los modelos computables de equilibrio general (CGE), aunque en realidad los dos se nutren de la misma base conceptual y analítica. Lo único que hay que hacer es utilizarlos correctamente porque ambos métodos tienen sus limitaciones dependiendo de para qué se utilizan y con qué intención (aquí). Para muchas intervenciones, el ACB es suficiente y menos costoso que construir un modelo CGE específico. La agregación que caracteriza al modelo CGE estándar concebido para analizar grandes shocks en la economía (por ejemplo, liberalización del comercio) suelen ser de poca utilidad para intervenciones específicas. Un modelo CGE concebido para shocks macroeconómicos (con sus tablas input-output nacionales) es incapaz de discriminar, por ejemplo, entre los efectos de una inversión en infraestructuras ferroviarias interurbanas y urbanas.

Hemos afirmado que el ACB no es sinónimo de estudio de impacto y que lo que trata de cuantificar es el efecto neto en bienestar. También hay que recalcar que la aproximación a la evaluación de la intervención es incremental. Sólo cuentan los cambios netos, no la relocalización de actividad (equidad al margen), y todos los cambios cuentan, no solo los del mercado directo sino de otros mercados secundarios sujetos a distorsiones, que se ven afectados de manera significativamente diferente con relación al contrafactual.

La ley recientemente aprobada sobre la institucionalización de la evaluación de políticas públicas defiende la función social de la evaluación y su utilización en la Administración Pública española como procedimiento habitual, incluyendo la creación de una agencia independiente de evaluación. Bienvenida sea, aunque como economistas recalcitrantes no podemos cerrar esta entrada sin llamar la atención sobre las imprecisiones e indefiniciones que contiene la ley con respecto a lo que es la evaluación económica, y como llevarla a cabo; así como la poca independencia real que contempla la ley para aislar de las presiones políticas a los futuros responsable de la evaluación en España (véase el debate aquí).

[1] El informe técnico, encargado a los autores por la Autoridad Independiente de Responsabilidad Fiscal (AIReF) para el Spending Review en Infraestructuras de Transporte 2018-2021, fue financiado por la Unión Europea a través del Programa de Apoyo a las Reformas Estructurales (SRSS). Dicho informe refleja únicamente las opiniones de los autores y no implica una posición política de la Comisión Europea o de la AIReF.

por Javier Campos

Javier Campos

• 
  

Javier Campos es profesor de Análisis de Mercados y Análisis de Empresas en la Universidad de Las Palmas de Gran Canaria. Doctor en Economía (ULPGC) y MSc in Economics (LSE). Ha trabajado en el Banco Mundial y en el Banco Interamericano de Desarrollo. Su investigación se centra en las áreas de Economía Industrial, Economía del Transporte y la Evaluación de Proyectos, tanto en Europa como en América Latina.

 Tiene la política monetaria efectos a LP? by Jordà, Singh & Alan M. Taylor

-  Si,a muy largo plazo 

 -sobretodo en Capital y productividad 

- más en las subidas de tipos que en las bajadas

https://www.frbsf.org/economic-research/publications/economic-letter/2023/september/does-monetary-policy-have-long-run-effects/

Does Monetary Policy Have Long-Run Effects?

Òscar Jordà, Sanjay R. Singh, and Alan M. Taylor

Monetary policy is often regarded as having only temporary effects on the economy, moderating the expansions and contractions that make up the business cycle. However, it is possible for monetary policy to affect an economy’s long-run trajectory. Analyzing cross-country data for a set of large national economies since 1900 suggests that tight monetary policy can reduce potential output even after a decade. By contrast, loose monetary policy does not appear to raise long-run potential. Such effects may be important for assessing the preferred stance of monetary policy.

---

Monetary policy has traditionally been regarded as being “neutral” in the long run. This means that the path of an economy over time is determined by factors other than what the central bank does, including the availability of workers and capital and how productively they can be combined. Monetary policy has generally been viewed as having a moderating influence on cyclical economic fluctuations. Its long-run effects are believed to be limited to nominal variables, such as prices and nominal interest rates.

In this Economic Letter, we examine the long-run implications of monetary policy for the productive capacity of the economy. Using cross-country data for a set of large national economies over the past century, we assess situations when an economy’s productive potential is different than it would otherwise be due to previous monetary interventions. We find that these long-run effects develop primarily through investment decisions that ultimately result in lower productivity and lower capital stock than would be available without policy intervention. These productivity effects persist for at least 12 years following a period of monetary policy tightening.

Policy effects in the short and long run

Traditional theories of how national economies work typically assume that monetary policy is neutral in the long run (for example, Lucas 1996; see Cerra, Fatás, and Saxena 2023 for a more recent literature review). That is, central bank actions such as lowering policy interest rates cannot be used to stimulate the economy indefinitely. Similarly, conventional wisdom implies that tightening policy by raising interest rates might only have temporary consequences for keeping economies running at a healthy pace. In this view, when inflation rises above a central bank’s target, policymakers may be less concerned about the risk of overtightening policy since the costs of doing so are temporary.

Our recent research in Jordà, Singh, and Taylor (2023) casts doubt on this traditional belief. To understand the situations in which monetary policy could have long-term effects, our work described in this Letter delves into historical data to describe how economies grow.

Broadly speaking, three factors determine an economy’s productive potential (see Basu and Fernald 2002). The first two are how much capital is available in an economy and how much labor there is to operate that capital. The more workers and the more machines are available, the more the potential output. The third factor is total factor productivity (TFP), which can be thought of as how cleverly existing stocks of capital and labor can be combined to obtain more output. The more TFP improves, the more the economy can produce, even if no new workers and no new machines are added. TFP growth is therefore a critical driver of economic growth.

How might interest rates affect an economy’s productive potential? Consider two examples. First, think of research and development (R&D) investment. In most cases, interest rates determine how much a business is willing to invest in increasing its capital and how much to invest in R&D, which is a good way to improve TFP. Higher interest rates slow down economic activity and tighten credit conditions; in turn, businesses tend to cut investments in all categories, including R&D (Moran and Queralto 2018). So, a potential mechanism for high interest rates to reduce the economy’s potential is through a reduction of R&D investment. A second example is known as labor scarring. When workers are laid off, their human capital depreciates the longer they remain unemployed. Thus, a slowdown in economic activity due to higher interest rates could generate a loss of the total skill level in the economy. These two simple examples illustrate a different view of how the economy’s potential can be hampered by monetary policy.

Measuring the effects of monetary policy

A key challenge for analyzing data on the macroeconomy is isolating the relationships between economic variables that represent causation rather than correlation. If interest rates are raised when the economy is buoyant and inflation is rising, a simple correlation analysis could mistakenly suggest that high interest rates cause high inflation. In reality, interest rates are typically high because the central bank is trying to bring inflation down. Accounting for such reverse causality in macroeconomic data is crucial for understanding business cycle dynamics and the influence of monetary policy.

The approach we use to separate causation from correlation is based on a simple idea from international economics. Over the past century or more, smaller economies have sometimes pegged their exchange rate to the currency of a bigger economy, usually referred to as the base. In that scenario, the returns on assets with similar risk characteristics will move at a similar pace between the pegging and the base economies. Otherwise, if money is free to flow across borders, investors will borrow where interest rates are low and invest where interest rates are high, eventually equalizing rates in both economies. This is called an arbitrage opportunity, and the mechanism we just described is usually called the trilemma of international finance.

Thus, when the base economy changes interest rates in response to domestic economic conditions, interest rates in the pegging economy will move in tandem, even if that economy’s domestic conditions do not require such an adjustment to interest rates. We use these externally driven interest rate movements as a source of random variation in monetary policy for the pegging economy. Because the change in financial conditions is independent of economic conditions in the pegging country, the resulting impacts are more likely to reflect causation rather than correlation.

We rely on this observation between base and pegging interest rates for our empirical analysis. Using annual data for 17 advanced economies over the period 1900 to 2015 excluding the two World Wars, we estimate how output and its components—labor, capital, and TFP—respond to movements in interest rates generated outside the pegging economy’s borders. We specifically assess the effects of an unexpected increase in interest rates by 1%. We then trace the responses of output, labor, capital, and TFP over the next 12 years. Output is measured as real GDP. Labor is measured as total hours worked, capital stock is constructed from investment in machines and buildings, and TFP is a residual from an aggregate production function using capital and labor as inputs.

Figure 1 show that unexpected changes in monetary policy, known as shocks, can slow the pace of economic activity much more persistently than is commonly believed, all other economic factors being equal. For example, panel A shows that, in response to a 1% increase in interest rates, output would be about 5% lower after 12 years than it would otherwise be. To provide some context for these numbers, consider some data for the United States. A 5% decline in the output trend caused by the monetary intervention relative to the pre-intervention trend would reduce an individual’s income by $3,000 in today’s dollars on average.

Figure 1
Average responses to 1% unexpected increase in policy interest rate: 1900-2015

Note: Responses to a 1% unexpected change in domestic short-term interest rate. Full sample: 1900–2015, World Wars excluded. In panel A, darker shading indicates one-standard-error and lighter shading indicates two-standard-error confidence bands around average. See Jordà, Singh, and Taylor (2023) for estimation details.

Panel B of Figure 1 breaks down the response of output into subcomponents of an aggregate production function. In response to a similar 1% increase in interest rates, after 12 years TFP would be about 3% lower and capital would be about 4% lower. However, labor would be about the same as the pre-shock trend. One plausible way to explain this is by considering a model of endogenous growth where investment in R&D determines TFP growth but labor demand is stable over the long run (Fornaro and Wolf 2023). In response to a monetary tightening, investment in productive ideas would fall, slowing TFP growth temporarily. This temporary growth slowdown accumulates to a lower trend level of TFP after the shock abates. Labor, on the other hand, returns to the pre-shock trend because labor usage in the long run is unaffected by the trend level of TFP.

No free lunch

If raising interest rates can have such costs in terms of the longer-run capacity of the economy, what about lowering rates: can a central bank boost the economy’s long-run potential with more accommodative monetary policy through lower interest rates?

Figure 2 shows that this is not the case. When we separate our interest rate experiments into those that resulted in rate hikes versus those that resulted in lower interest rates, we see that there is no free lunch. That is, a central bank might not be able to undo the long-run effects on the economy’s potential by running the economy hot. The blue line shows that lower interest rates have mostly temporary effects that vanish after a few years, as traditional theories predict. However, the red line reinforces the results from Figure 1 that show an increase in interest rates casts a long shadow on the economy.

Figure 2
Real GDP response to unexpected policy rate changes

Note: Responses to a 1% unexpected change in domestic short-term interest rate. Full sample: 1900–2015, World Wars excluded. Shading indicates one-standard-error confidence bands around each average. See Jordà, Singh, and Taylor (2023) for estimation details.

Among the usual caveats to any empirical analysis, we should emphasize that, in our sample, the United States is usually a base economy that other countries peg their currencies to. Therefore, our findings mostly reflect the experiences of pegging economies, not that of the United States. However, in Jordà, Singh, and Taylor (2023) we find evidence using additional data sets, experiments, and methods that suggests similar long-lasting effects for the United States as the ones we report here.

Conclusion

What lessons should we take away from our analysis in this Letter? In line with traditional thought, monetary policy aims at having the economy grow to its potential while keeping inflation low and stable. Our results suggest that a challenge for monetary policy is that, in addition to the effects on current economic activity, variations in policy rates can have unintended lingering effects on potential growth, which may ultimately complicate the calibration of policy.

Òscar Jordà
Senior Policy Advisor, Economic Research Department, Federal Reserve Bank of San Francisco

Sanjay R. Singh
Senior Economist, Economic Research Department, Federal Reserve Bank of San Francisco

Alan M. Taylor
Professor, University of California, Davis, and Visiting Scholar, Federal Reserve Bank of San Francisco

References

Basu, Susanto, and John G. Fernald. 2002. “Aggregate Productivity and Aggregate Technology.” European Economic Review 46(6), pp. 963–991.

Cerra, Valerie, Antonio Fatás, and Sweta C. Saxena. 2023. “Hysteresis and Business Cycles.” Journal of Economic Literature 61(1), pp. 181–225

Fornaro, Luca, and Martin Wolf. 2023. “The Scars of Supply Shocks: Implications for Monetary Policy.” Journal of Monetary Economics, forthcoming.

Jordà, Òscar, Sanjay R Singh, and Alan M Taylor. 2023. “The Long-Run Effects of Monetary Policy.” FRB San Francisco Working Paper 2020-01.

Lucas, Robert E., Jr. 1996. “Nobel Lecture: Monetary Neutrality.” Journal of Political Economy 104(4), pp. 661–682.

Moran, Patrick, and Albert Queralto. 2018. “Innovation, Productivity, and Monetary Policy.” Journal of Monetary Economics 93, pp. 24–41.

Opinions expressed in FRBSF Economic Letter do not necessarily reflect the views of the management of the Federal Reserve Bank of San Francisco or of the Board of Governors of the Federal Reserve System. This publication is edited by Anita Todd and Karen Barnes. Permission to reprint must be obtained in writing.

 

 

 Lectura introductoria muy útil para curso avanzado de macro (y para poder hablar de macro más allá de cansinas controversias entre "escuelas de pensamiento"

Macroeconomic Research, Present and Past

Abstract

How is macroeconomic research conducted and what is it trying to accomplish? We explore these questions using information gleaned from 1,894 articles published in 10 leading journals. The emphasis on quantitative, computation-intensive theory-based analysis has grown over the past 40 years, while the use of econometric methods to test economic hypotheses has diminished. Applied micro techniques and micro data have displaced time series methods. Market imperfections are pervasive and financial frictions have received increasing attention in the past 10 years. The frequency with which non-macro JEL codes appear in macro articles indicates a great deal of overlap between macroeconomics and other fields.

Citation

Glandon, P. J., Ken Kuttner, Sandeep Mazumder, and Caleb Stroup. 2023. "Macroeconomic Research, Present and Past." Journal of Economic Literature, 61 (3): 1088-1126. DOI: 10.1257/jel.20211609

 

• P. J. Glandon
• Ken Kuttner
• Sandeep Mazumder
• Caleb Stroup 
• https://www.aeaweb.org/articles?id=10.1257/jel.20211609