Antonio Paradiso

The dynamics of Italian public debt: alternative paths for fiscal consolidation

This article analyses possible targets for the Italian debt-to-GDP ratio with a small macroeconomic model. The role of international macroeconomic variables such as the US GDP growth, prices of raw materials, EUR/USD exchange rate and European Central Bank (ECB) monetary policy stance and domestic policy instruments is analysed in the debt dynamics. We find that external conditions play a fundamental role for the Italian fiscal consolidation. To reach a target of 100% of debt-to-GDP ratio by 2020, a further growth-sustaining policy has to be implemented.

How to offset the negative trend growth rate in the Italian economy

The trend growth rate of the Italian economy has been declining since the 1980s. To examine how to offset this trend, we estimate a simple specification of an endogenous growth model. Cointegrating equations for the long-run output growth and its determinants are estimated with alternative time series methods. Our results imply that policies to double trade openness are necessary.

Are Italian consumer confidence adjustments asymmetric? A macroeconomic and psychological motives approach

This paper estimates the determinants of Italian consumer confidence indicator (CCI) using time series methods. We find there exists a long-run relationship between CCI and its determinants when an important political event ‘operation clean hands’, captured by a dummy, is considered. Using the asymmetric error correction model (Enders & Siklos, 2001), we find that consumers respond asymmetrically to different types of disequilibrium error under threshold autoregressive (TAR) adjustment specification. These findings are consistent with the psychological bias approach (Bovi, 2009).

A New Keynesian IS Curve for Australia: Is it Forward Looking or Backward Looking?

This article estimates the forward looking, backward looking and an extended version of the New Keynesian IS curve for Australia. The validity of these models is investigated by imposing the constraint on real rate of interest as well as when the constraint is relaxed. Two measures of output gap, namely GAP1 (constructed using the unobserved components approach) and GAP2 (constructed using a quadratic trend) are utilized. Our results suggest that the baseline backward looking and forward looking models are overwhelmingly rejected by the data. This evidence strongly supports the extended backward looking model (with GAP2) being relevant for monetary policy analysis.

A Financial Sector Balance Approach and the Cyclical Dynamics of the U.S. Economy

This paper investigates the relationship between asset markets and business cycles with regard to the United States economy. We consider the Goldman Sachs approach (2003) developed to study the dynamics of financial balances. By means of a small econometric model we find that asset market dynamics are fundamental to determining the long-run financial sector balance dynamics. The gap between long-run equilibrium values and the actual values of the financial balances help to explain the cyclical path of the economy. Among all financial sectors balances, the financing gap in the corporate sector shows a leading effect on business cycles, in a Minskyan spirit. The last results appear innovative with respect to Goldman Sachss findings. Furthermore, our econometric results are robust and quite stable.

Private sector balance, financial markets, and US cycle: a SVAR analysis

Purpose – Considering the sectoral balance approach of Godley, and focusing only on the two main components of the private sector balance for the U.S. economy (household and non-financial corporate balance), we investigate the relationship between these two sectors, the financial variables, and economic cycle. In particular, we consider all these relationships endogenously. Design/methodology/approach – We estimate a structural VAR model between household and (non-financial) corporate financial balances, financial markets, and economic cycle and we perform an impulse response analysis. All the variables are expressed as cyclical components applying the Hodrick-Prescott filter. Findings - The main result is that: (1) household and corporate balances react to financial markets in the way we expected and discussed; (2) the economic cycle influences the two financial balances; (3) the corporate balance has a positive impact on the cycle; (4) the economic cycle and financial balances influence the financial variables. In particular, point (3) shows that the corporate balance is a leading component of the cycle as suggested by Casadio and Paradiso (2009) and accords with Minsky’s theory of financial instability. Research limitations/implications – The analysis does not include the foreign sector (current-account balance). Originality/value – Our contribution is an important step forward with respect to the two main contributions in literature which use this approach: the Levy Institute macroeconomic team and Goldman Sachs. Methodologically their models are based on some assumptions (such as exogeneity or market clearing price mechanism for the financial markets) which we overcome considering all the relationships studied in an endogenous manner.

Do inequality, unemployment and deterrence affect crime over the long run?

ABSTRACT Do inequality, unemployment and deterrence affect crime over the long run? Regional Studies. This paper investigates the long-run relationship between crime, inequality, unemployment and deterrence using US state-level data from 1978 to 2013. The novelty is to use non-stationary panels with a factor structure. The results show that: (1) a crime-theoretical model fits the long-run relationship well; (2) income inequality and unemployment have a positive impact on crime, whereas that of deterrence is negative; (3) the effect of income inequality on crime is larger when inequality is measured on a wider population proportion; and (4) property crime is generally highly sensitive to the deterrence effect of police.

A quasi real-time leading indicator for the EU industrial production

We build a quasi real-time leading indicator (LI) for the EU industrial production (IP). Differently from previous studies, the technique developed in this paper gives rise to an ex-ante LI that is immune to “overlapping information drawbacks�?. In addition, the set of variables composing the LI relies on a two-steps dynamic and systematic procedure. This ensures that the choice of the variables is not driven by subjective views. Our LI anticipates swings (including the 2007-2008 crisis) in the EU industrial production – on average – by 2 to 3 months. If revised, its predictive power largely improves. Via a couple of standard empirical exercises we show that the proposed LI (i) forecasts crises’ phases better than the ex-post LIs proposed by the OECD and the Conference Board and (ii) captures the interest rate policy pattern rather well.

Financial Cyclical Factors and Growth: Insights from an Augmented Stochastic Solow Growth Model

We present an augmented stochastic version of the Solow neoclassical growth model to examine whether financial factors -- expressed as deviations from their trend -- represent important business cycle drivers.Our novel framework is used to study the dynamics of the US growth over the period 1890-2013. We find that financial cyclical factors played an important role in explaining output fluctuations in the US over the last century. By comparing different model specifications, we show that the role of each specific financial factor in explaining growth changes over time generating models instability. Taken together, our results have implications for the effectiveness of medium-term policy interventions.Accounting for such cyclical factors is thus relevant for policymakers.

Common Trends in the US State-Level Crime. What Do Panel Data Say?

This paper aims to investigate the long-run relationship between crime, inequality, unemployment and deterrence using state-level data for the US over the period 1978- 2013. The novelty of the paper is to use non-stationary panels with factor structures. The results show that: i) a simple crime model well fits the long run relationship; ii) income inequality and unemployment have a positive impact on crime, whereas deterrence displays a negative sign; iii) the effect of income inequality on crime is large in magnitude; iv) property crime is generally highly sensitive to deterrence measures based upon police activities.