Inflation, uncertainty, and labour market conditions in the US

ABSTRACT

Recent inflation dynamics in the United States (US) questioned the role of driving forces of inflation in the long run. Although the US recorded one of the longest economic recovery periods and the labour market conditions improved after the Global crisis from 2008 to 2009, the inflation level remained relatively low. Starting from this evidence, the purpose of our paper is to shed light to the influence of inflation uncertainty and labour market conditions on the US inflation level. To this end, we use two bounded measures of inflation uncertainty, and we compare a linear with an asymmetric Autoregressive Distributed Lag (ARDL) framework. We show that both inflation uncertainty and labour market conditions explain the long-run US inflation. However, these results are sensitive to the way the inflation uncertainty is computed. Moreover, contrary to the recent affirmations regarding the vanishing role of labour market in explaining the US inflation in the long run, we show that the labour market influence is stronger in the post-crisis, compared with the pre-crisis period. Therefore, the monetary policymakers cannot make abstraction of labour market developments in anticipating the US inflation level.

KEYWORDS:

• US inflation
• inflation uncertainty
• labour market
• bounded series
• NARDL

JEL CLASSIFICATION:

• C22
• E24
• E31
• E58

Notes

¹ According to the FRED database, the inflation rate shifted from 6% in 1973 to more than 10% in 1974, while the US economic contraction installed since 1974 (−0.5%). At the same time, the unemployment rate in the US increased from 4.9% in 1973 to 5.6% in 1974, and afterwards, to 8.5% in 1975.

² Please refer to the recent papers of Albulescu et al. (2019), Balcilar and Özdemir (2013), Caporale, Onorante, and Paesani (2012), Chen, Shen, and Xie (2006), Chowdhury (2014), Ferreira and Palma (2016), Jiang (2016), Keskek and Orhan (2010).

³ The question was raised during the speech delivered on 26 September 2017 at the 59^th Annual Meeting of the National Association for Business Economics in Cleveland.

⁴ The Bureau of Labour Statistics shows that the unemployment rate in the US diminished from 9.6% in 2010, to 4.4% in 2017.

⁵ According to Thornton (2012), the Federal Reserve implemented a de facto inflation-targeting regime after the Global crisis from 2008 to 2009.

⁶ Starting from January 2012, the Federal Open Market Committee’s long-run inflation objective was established at 2%.

⁷ Backdated data series are available starting with 1976.

⁸ The timespan is restricted by the LMCI computation, starting with 1976M08. In July 2017, the Board started to discontinue update the index. Therefore, our LMCI series stop in 2017M06.

⁹ For robustness purpose and according to Albulescu et al. (2019) and Ferreira and Palma (2016), we have computed the month-on-month percent change in CPI (${\pi }_{\mathrm{m}-\mathrm{o}-\mathrm{m}}$), using the formula $1200\times \mathrm{l}\mathrm{n}(\frac{\mathrm{C}\mathrm{P}{\mathrm{I}}_{\mathrm{t}}}{\mathrm{C}\mathrm{P}{\mathrm{I}}_{\mathrm{t}-1}})$. Calculated this way, the inflation series (our dependent variable) become stationary, generating a potential bias in the cointegration estimations (for additional explanations, please refer to Pesaran, Shin, and Smith 2001). Therefore, we have decided not to use the month-on-month inflation in our ARDL estimations.

¹⁰ In addition, all variables present a nonlinear nature, as indicated by the BDS test (Brock, Dechert, and Scheinkman 1996) – Table A1 (Appendix).

¹¹ See the critic of Evans (1991) showing that higher volatility does not necessarily mean higher inflation uncertainty.

¹² The advantages of using the NARDL approach by Shin, Yu, and Greenwood-Nimmo (2014) are carefully explained by Alsamara et al. (2017) and Hemrit and Benlagha (2020).

¹³ Pesaran, Shin, and Smith (2001) show that ARDL models are free from residual correlation. Therefore, there are not endogeneity issues related to appropriate lag selection.

¹⁴ F-statistic = 146.9 with the associated p-value = 0.000.

Additional information

Funding

This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS–UEFISCDI, project number PN-III-P1-1.1-TE-2016-0142.