Time–frequency characterization of the U.S. financial cycle

Verona, Fabio

doi:10.1016/j.econlet.2016.04.024

Cited by 62 publications

(31 citation statements)

References 17 publications

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“…The papers closely related to this work are Ramsey (2013a,b, 2014), Kilponen and Verona (2016) and Aguiar-Conraria, Martins and Soares (2018). Using CWT tools, Gallegati and Ramsey (2013a) analyse the time-frequency correlation between investment and two measures of Q (equity Q and bond Q).…”

Section: Wavelets In Economicsmentioning

confidence: 98%

“…3 The continuous wavelet transform (CWT) is becoming a popular tool in econometric analysis.The most common argument for using the CWT is the possibility of simultaneously assessing how variables are related at different frequencies and how these relationships have changed over time. For instance, the CWT is well suited to study the interaction between variables (macro/financial) and cycles (business/credit) that fluctuate at different frequencies (see Verona, 2016).…”

Section: Wavelets In Economicsmentioning

confidence: 99%

“… Other contributions using CWT analysis include Rua (), Aguiar‐Conraria, Martins and Soares (, ), Verona () and Aguiar‐Conraria, Soares and Sousa () (the latter paper also makes use of the concepts of partial phase‐differences and partial gains). The early papers in economics using wavelets (Ramsey and Lampart, ,b) rely on the discrete wavelet transform.…”

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confidence: 99%

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Investment, Tobin's Q, and Cash Flow Across Time and Frequencies

Verona

2019

Oxf Bull Econ Stat

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The investment literature has long acknowledged the time‐ and frequency‐varying dynamics of the relationship between investment, Tobin's Q and cash flow. In this paper, we use continuous wavelet tools to estimate and assess the relationship between these variables simultaneously at different frequencies and over time. We find that (i) Q and cash flow are complementary sources of information for investment, the former being more important for firms’ investment decisions in the medium‐to‐long run and the latter at business cycles frequencies; and (ii) investment‐Q sensitivity declines over time at all frequencies, while investment–cash flow sensitivity declines at business cycles frequencies but remains largely stable over the medium‐to‐long run.

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Section: Wavelets In Economicsmentioning

confidence: 98%

Section: Wavelets In Economicsmentioning

confidence: 99%

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Investment, Tobin's Q, and Cash Flow Across Time and Frequencies

Verona

2019

Oxf Bull Econ Stat

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“…Verona, 2016; Ardila and Sornette, 2016. Harding and Pagan (2002, 2006, 2016 suggest using a dating algorithm introduced by Bry and Boschan (1971), adapted for quarterly data and termed the BBQ rule 11 : The steps for this analysis are as follows (Harding and Pagan, 2016):…”

Section: Model-based Approachesmentioning

confidence: 99%

Measuring the Financial Cycle in South Africa

Farrell

Kemp

2020

South African J Economics

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We measure the financial cycle of South Africa using three different methodologies. The financial cycle is identified using credit, house prices and equity prices as indicators, and estimated using traditional turning-point analysis, frequency-based filters and an unobserved components modelbased approach. We then consider the financial cycle's main characteristics and examine its relationships with the business cycle. We confirm the presence of a financial cycle in South Africa that has a longer duration and a larger amplitude than the traditional business cycle. Developments in measures of credit and house prices are important indicators of the financial cycle, although the case for including equity prices in the measures is less certain. Periods where financial conditions are stressed are associated with peaks in the financial cycle, suggesting that the estimated financial cycle may have similar leading indicator properties to financial conditions or stress indices. JEL Classification: E44, E61, G21

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“…Although widely accepted in the physical and medical sciences, wavelet analysis has been slow to enter the toolbox of methods used in empirical economics, but this is now being addressed by numerous recent contributions. Examples include Aguiar‐Conraria and Soares (), Gallegati et al (), Dar et al (), Tiwari et al (), Chen (), Crowley and Hughes Hallett (), Faria and Verona (), Verona (), and specifically for South African core inflation, Du Plessis et al ().…”

Section: Modwt Wavelet Analysis Data and Backgroundmentioning

confidence: 99%

Evaluating South African Fiscal and Monetary Policy Trade‐offs Using a Wavelet‐Based Model

Crowley

Hudgins

2018

South African J Economics

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The balance between South African fiscal and monetary policy in an open economy context poses some interesting questions for policymakers: questions such as whether more aggressive monetary or fiscal policy will likely deliver better growth prospects in the short and medium run, and what will the consequences be for the real exchange rate and for inflation? This research applies wavelet analysis to post‐apartheid South African quarterly macroeconomic data, and uses the decomposition to simulate a large state‐space linear‐quadratic tracking model. We find that restricted fiscal policy is the best option to realise growth, leading to lower interest rates, lower inflation, real exchange depreciation and improved trade balances compared to restricted monetary policy.

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Time–frequency characterization of the U.S. financial cycle

Cited by 62 publications

References 17 publications

Investment, Tobin's Q, and Cash Flow Across Time and Frequencies

Investment, Tobin's Q, and Cash Flow Across Time and Frequencies

Measuring the Financial Cycle in South Africa

Evaluating South African Fiscal and Monetary Policy Trade‐offs Using a Wavelet‐Based Model

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