Natalie Burr
The challenge of measuring financial conditions
Imagine you were tasked with thinking about how financial conditions have changed over a policy tightening cycle. Different economists would come to very different conclusions, and none would necessarily be wrong. Why? Because measuring financial conditions is challenging – for a variety of reasons. A financial conditions index (FCI) is a common solution, and its advantage lies in the disadvantage of the alternative: it is simpler than making a judgement across a range of individual variables. In this post, I propose one method to create a UK FCI. I find that financial conditions have tightened significantly over the past two years, coming from a period of accommodative conditions following Covid.
What are financial conditions?
Generally financial conditions are defined as the ease with which households and firms can gain access to financing. But FCIs can also be used as an (imperfect) measure of the effectiveness of the first stage of the monetary transmission mechanism. Imperfect because factors other than monetary policy can also influence financial conditions, but useful nevertheless to assess how effectively changes in policy rates are feeding through to financial markets, such as money market interest rates, credit spreads, asset prices, risk premia and the exchange rate.
How do you measure financial conditions?
When it comes to the choice of methodology, there are generally two ‘strands’ of FCIs. Some indices have economic interpretation, where the weights of individual components depend on their historical comovement with macroeconomic variables like GDP, or inflation. Other indices use a data-driven approach, deriving the weights statistically. My new FCI falls within the latter group. The advantage over the first group of indicators is that it does not impose a static relationship between financial conditions and GDP. I argue that while making this connection is helpful, these indices risk trying to achieve too much in just one index. The assumption that the relationship between financial and credit variables, and GDP are constant over time is a strong one. In reality, these relationships can be time-varying, and state-dependent.
Methodology
I offer an FCI for the UK constructed using principal component analysis (PCA), inspired by Angelopoulou et al (2013). Why PCA? The definition of financial conditions can incorporate a broad range of variables. PCA is a dimensionality reduction technique which decomposes the covariance structure of selected series into factors that are common to all, and idiosyncratic noise. PCA is simple and intuitive, allowing to combine a set of explanatory variables that are closely related, optimising the information embodied in the input variables. The choice of methodology was motivated by insights from Arrigoni et al (2020), who find that simpler financial conditions measures perform better than sophisticated statistical methods.
The index uses monthly data on a range of short and long-term nominal government bond yields, term spreads (the difference between some short and long-term yields), credit spreads (mortgage and unsecured lending), the exchange rate and risky asset prices. The data selection is motivated by the asset prices and credit variables that likely matter for economic activity. Risky asset prices matter due to wealth effects which affect spending decisions, and represent the cost of market-based financing to firms. A wide range of interest rates (including mortgage rates) matter because they represent the cost of borrowing firms and households face. In much the same way, the exchange rate matters as it represents the cost, in £, of other currencies. The question is, what information matters most for aggregate financial conditions? That is what PCA can help with.
First, I prepare the data for analysis. The index contributes to the literature of existing FCIs by addressing the issue of non-stationarity. Stationarity of inputs is important particularly for the FCI to have a reasonable interpretation over a longer period of time. I purge these trends by subtracting an estimate of the long-run equilibrium real interest rate (r*) from interest rates, and applying log differences to equity prices. Long run, structural factors that are not directly relevant for financial conditions have driven these trends, and these would otherwise imply a continuous loosening of financial conditions over time. By detrending, I ensure a reasonable interpretation of the index, which I discuss in the next few paragraphs.
Second, the variables entering the PCA have very different magnitudes and units. Therefore, all variables are standardised by subtracting the mean and dividing by their standard deviation. Lastly, variables are also normalised to account for the way in which the series affect financial conditions. In order for an increase in the FCI to denote a tightening in financial conditions, variables where an increase reflects a loosening in financial conditions enter the model with an inverted sign.
Finally, the index is compiled using weights implied by the first three principal components (which explain almost 80% of the overall variation in the data) on the normalised variables. Chart 1 shows the index, and a decomposition into the contribution from various groups of variables. Financial conditions have tightened sharply over the latest tightening cycle, but moves have retraced somewhat since a spike in September 2022, on account of falling yields and Sterling appreciation.
Chart 1: A new UK financial conditions index
Sources: Bloomberg Finance L.P., Moneyfacts, Refinitiv Eikon from LSEG, Tradeweb and Bank calculations. Latest observation: January 2023.
By scaling the index to be mean-zero, the index should be interpreted as a relative, not an absolute measure of financial conditions. Although an increase (decrease) in the index denotes a tightening (loosening) in financial conditions, it is unclear to what extent they are ‘tight’ or ‘loose’ in absolute terms. In other words, financial conditions above 0 are tight conditions only relative to the historical average.
Similar to existing FCIs, it is not a perfect, or holistic measure of financial conditions. This index is very much a reduced form measure and does not tell us anything about ‘why’, for example, interest rates rise and fall. Individual variables have not been purged of their responses to macroeconomic variables (due to the difficultly of doing this accurately), and therefore the index does not capture pure exogenous shifts in financial conditions. Moves may be endogenous to changes in the macroeconomic environment or monetary policy, and movements in asset prices attributed solely to macroeconomic shocks are not necessarily meaningful changes in financial conditions.
A thought experiment
This index was built on the premise that financial conditions are very hard to measure. Staying true to the belief that one index cannot provide the final word, I test three alternative specifications of the index.
First, I do not allow the weights to be time-varying, so they are not generally robust to changes in the sample. I therefore re-estimate the index only over a post-financial crisis (GFC) sample period, shown in Chart 2. Conditions appear tighter in the aftermath of the GFC, where spreads and a steepening yield curve contribute the most. But since the Brexit referendum in 2016, when the Bank cut interest rates and undertook QE, the index loosens relative to historical experience.
Chart 2: UK FCI estimated over a post-financial crisis sample period
Notes: Solid line represents the post-GFC, dotted line shows Chart 1 version.
Sources: Bloomberg Finance L.P., Moneyfacts, Refinitiv Eikon from LSEG, Tradeweb and Bank calculations. Latest observation: January 2023.
Second, I explore a ‘real’ version of the index, which uses real interest rate variables, exchange rate and equity prices. Chart 3 shows that in real terms, financial conditions have tightened less, reflecting the fact that real interest rates in the latest tightening cycles are still largely in negative territory.
Chart 3: A ‘real’ UK financial conditions index
Sources: Bloomberg Finance L.P., Moneyfacts, Refinitiv Eikon from LSEG, Tradeweb and Bank calculations. Latest observation: December 2022.
Finally, I explore a version of the index that strips out the effects, on both interest rates and equity prices, of international spillovers. I use model-based estimates that are identified through the heteroscedasticity of asset prices, which pin down the geographic origin of the underlying shocks. Comparing the post-GFC FCI (dotted) and the FCI excluding spillovers (solid line) in Chart 4, international spillovers (mainly US and EA) have slowed the relative tightening of UK financial conditions over 2021, but softened the spike in financial conditions around the mini-budget turmoil of September 2022.
Chart 4: A UK financial conditions index, stripping out international spillovers
Notes: Solid line represents the FCI excluding spillovers, dotted line shows the post-GFC version.
Sources: Bloomberg Finance L.P., Moneyfacts, Refinitiv Eikon from LSEG, Tradeweb and Bank calculations. Latest observation: January 2023.
Having looked at a variety of specifications, Chart 5 brings back the link to policymaking, by portraying the relationship between financial conditions and Bank Rate, focusing on tightening cycles in the UK since the Bank’s operational independence in 1997. For each episode, I fit a linear trend to illustrate the relationship. There are reasonable arguments as to why this relationship may not be linear, not least the different pace, speed and size of hikes. But broadly speaking, tightening Bank Rate has been associated with tightening financial conditions (with the exception of the early period of operational independence). And in the latest tightening cycle, each unit of Bank Rate increase had brought a considerable amount of tightening, more so even than in previous cycles.
Chart 5: Scatter plot of UK financial conditions index against Bank Rate over past tightening cycles
Notes: For the 2021–22 hiking cycle, two observations (denoted by the grey diamonds) were excluded from the estimation of the linear trend. These are observations for September and October 2022, which are likely to be influenced by the mini-budget turmoil in September 2022. The FCI used for this chart is one presented in Chart 1.
Sources: Bloomberg Finance L.P., Moneyfacts, Refinitiv Eikon from LSEG, Tradeweb and Bank calculations. Latest observation: January 2023.
To sum up, financial conditions is a tough concept to capture in just one index. I have argued that FCIs are nevertheless useful, to assess how changes in policy rates transmit to aggregate financial conditions. I find that UK financial conditions have tightened significantly over the most recent tightening cycle, but the degree of tightening is subject to much uncertainty. Robustness checks undertaken by looking at different variations of the FCI demonstrate this. Therefore, it is important to focus on a variety of indices to make a robust and holistic assessment of financial conditions.
Natalie Burr works in the Bank’s External MPC Unit.
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