samchain/econo-pairs-v1 huggingface dataset:
Option-adjusted spread on index of high-yield bonds issued in the US and spread to maturity on index of leveraged loans issued in the US measured relative to the spot Treasury curve. 9  Graham and Leary (2011), Harris and Raviv (1991). Atkinson (1967), Bernanke et al. (1996), Greenwood and Hanson (2013). 11 The characteristic feature of cov-lite loans is not that they have fewer covenants, but that the requirements bind less often, and in particular only in response to particular events (such as additional financing). More traditional, “cov-heavy” contracts require firms to meet such requirements continually (Becker and Ivashina (2016)). 10  15  All speeches are available online at www.bankofengland.co.uk/speeches  15  If you think there are parallels here with the subprime mortgage boom in the U.S., ahead of the last crisis, then you’d be right. Those too were grouped together and sold to investors as packages of loans, diluting the ability and incentive to monitor individual risks; they grew extremely rapidly, particularly in the last year or two of the boom – and, as it happens, they accounted at the peak for a similar share of their underlying market (13% of total U.S mortgage debt). We should recognise that, in aggregate, corporate leverage in the UK has fallen since the crisis (Chart 17, which includes bonds as well as bank loans).12 As with mortgages, interest payments on those debts remain well below average and, if bond markets are anything to go by, will remain so for quite a while yet.

They are now used by most car buyers, including (one presumes) those who are overall savers. According to the government the majority of student loans will not be fully repaid (the ONS has recently decided that most of it should therefore be re-allocated to the government, an accounting change planned for later this year.) Taken together, car finance and student loans account for almost all the rise in households’ unsecured gearing in recent years, as currently measured. The remainder – comprising the more conventional credit card balances, consumer loans and overdrafts – is plotted in blue in Chart 5. It hasn’t grown much and is pretty much the same as it was, relative to income, in the mid-1990s. 2  You might, however, expect to see them in first differences (i.e. in the growth rate of debt), as these could help cleanse the data of enduring country-specific differences in the sustainable level of debt.
With no reciprocity, although 𝜙𝑠𝐻 = −6, the foreign banks’ market share and leakage are calibrated jointly as 𝜙𝐹 𝑓  1  𝑠 ( 𝐻 (1−𝑓) = − ), a leakage of one-third, in line with the estimate of Aiyar et al (2014). And 𝑘1𝐹 = 0, so that the  𝜙𝑠  3  13  All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx  13  increase in resilience is proportional to the amount of domestic credit provided by domestic banks: this is set as 𝑓 = 0.11, also in line with Aiyar et al (2014). Both channels make the CCyB less effective without reciprocity. The credit leakage makes the leaning channel one-third smaller, while the assumption that resilience is lower when foreign banks hold less capital against domestic credit makes the resilience channel 11% smaller. In both the models with and without reciprocity, both countries are assumed to minimise loss functions analogous to those in appendix 2, containing only their own national objectives of inflation and output deviations, and the domestic crisis probability. 1  9)  𝐿 = (𝜋12 + 𝜆𝑦12 ) + (1 − 𝛾1 )𝛽𝐸1 𝐿2,𝑁𝐶 + 𝛾1 (1 + 𝜁)𝛽𝐸1 𝐿2,𝐶  10)  𝐿∗ = (𝜋1∗2 + 𝜆𝑦1∗2 ) + (1 − 𝛾1∗ )𝛽𝐸1 𝐿∗2,𝑁𝐶 + 𝛾1∗ (1 + 𝜁)𝛽𝐸1 𝐿∗2,𝐶  2  1 2  Domestic loss function Foreign loss function  Each policymaker takes the setting of the other’s policy as given when optimising according to their own individual loss function.

1)  𝑦1 = 𝐸1𝑃𝑆 𝑦2 − 𝜎(𝑖1 − 𝐸1𝑃𝑆 𝜋2 + 𝜔𝑠1 )  IS curve  2)  𝜋1 = 𝜅𝑦1 + 𝐸1𝑃𝑆 𝜋2 + 𝜈𝑠1  Phillips curve  3)  𝑠1 = 𝜓𝑘1  Banking sector credit spreads  4)  𝐵1𝐵 = 𝜙0 + 𝜙𝑖 𝑖1 + 𝜙𝑠𝐵 𝑠1 + 𝜉1𝐵  Banking sector real credit growth  5)  𝐵1𝑀 = 𝜙0 + 𝜙𝑖 𝑖1 + 𝜙𝑠𝑀 𝑠1 + 𝜉1𝑀  Market based sector real credit growth  6)  𝛾1𝐵 = (1 + (𝑒𝑥𝑝(ℎ0 + ℎ𝐵 𝐵1𝐵 + ℎ𝑘 𝑘1 ))−1 )−1  Banking sector crisis probability  7)  𝛾1𝑀 = (1 + (𝑒𝑥𝑝(ℎ0 + ℎ𝐵 𝐵1𝑀 ))−1 )−1  Market-based sector crisis probability  8)  𝛾1 = 𝑏𝛾1𝐵 + (1 − 𝑏)𝛾1𝑀  Total crisis probability  The IS and Phillips curves determine, respectively, output (𝑦1 ) and inflation (𝜋1 ), as functions of current and expected future output and inflation  17  and the policy interest rate (𝑖1 ). Output and inflation also depend on  banking sector credit spreads (𝑠1 ). Spreads push down on aggregate demand in the IS curve by increasing the interest facing borrowers in the economy. They also have a negative near-term effect on aggregate supply, raising inflation for a given level of output via an endogenous cost-push mechanism in the Phillips Curve.
These reforms are also intended to help address the tension between innovation in investments and underwriting, and the strong reliance on historic data in internal models. On reporting, we have already made some changes that significantly reduce the reporting burden for smaller / medium-sized firms. Both the Government and the PRA have engaged the industry on additional reforms that aim to further reduce burden on firms, particularly for returns that have not proved useful in practice. The Government published proposals in this area in its April Consultation Document and a further PRA consultation on additional reductions and improvements will follow later this year. Our intended changes to the MA application process aim to reduce barriers created to timely MA portfolio investment. These reforms could introduce a ‘two-lane’ process, where only more complex or precedent-setting assets would automatically be subject to a complete review prior to approval. Less complex assets could instead receive a streamlined review, wherein certain aspects of the review (such as internal ratings) could be deferred until after the initial approval. As for the internal model application process, safeguards could potentially be used to manage any risks introduced by these reforms to the MA application process. We are also considering potential changes to the MA breach framework, to soften the cliff-edge that currently exists, wherein the PRA must revoke full MA approval if a breach of eligibility conditions is unresolved after two months. This harsh penalty can act as a deterrent in firms’ investment decisions.

Earlier in the program, we ended up purchasing a large concentration of off-the-run securities, including bonds that were issued 15 to 25 years ago. Given their age, these bonds are generally less liquid and less valuable to market participants, and hence dealers were willing to sell them to us at cheaper prices relative to other securities. At more recent operations, however, we have received a greater share of offers to sell more recently issued Treasury securities, including on-the-run issues, and our purchases have shifted accordingly. This suggests that older, off-the-run securities may have become harder for dealers to obtain, and that they have increasingly found it appealing to offer more recent issues, which are available in greater supply and are generally more liquid. Our procedure allows this shift to take place, as long as the more recent issues are offered to us on generally favorable terms. Overall, the Desk has endeavored to implement the FOMC’s policy decisions in a manner that ensures competitive and appropriate prices for the securities obtained and that maintains the efficient functioning of financial markets. I believe that we have managed to accomplish these objectives with our operations to date. Market developments during the purchase programs Of course, the operational objectives discussed above do not speak to the broader policy objectives of the asset purchase programs.
Ideally, we want a regime in which we retain the benefits from the services provided by G-SIFIs to the economy, but not at the price of having to “bail-out” such institutions in order to preserve financial stability should they come to the brink of failure. I believe that a credible solution involves two complementary goals. First, coordinated steps must be taken to significantly reduce the likelihood that a G-SIFI ever reaches the point where it is at risk of failure. This risk should be pushed well below the level for smaller and less complex financial institutions. Second, home jurisdictions for these G-SIFIs need credible resolution mechanisms that can be implemented on a global basis so these firms can fail without large systemic consequences. A resolution mechanism will be credible only if it reduces the negative externalities from such a failure to an acceptable level. While progress has been made toward these two goals, additional work and coordination is still required. Turning first to efforts to reduce the likelihood that a G-SIFI will be at risk of failing, the Basel international standards raised both the quantity and quality of capital for internationally active banks. Banks also are required to capture more complex risks in their measures of risk-weighted assets. To complement the stronger risk-weighted capital standards, an international leverage ratio requirement also has been adopted. In addition, the Basel framework will require a capital buffer that increases with a firm’s size, complexity, interconnectedness and global footprint.

Two colleagues at the Bank, Fergus Cumming and Al Firrell, have recently used a database on all mortgages granted in the UK since 2005 to explore house-moving patterns.42 The results are preliminary, but let me share some of the early findings to demonstrate what might be feasible. Chart 19 plots the frequency of house moves at different distances in 2018. The modal distance of a house move is less than 10km. This is twice as likely as the second most popular distance – 10-20km. In other words, a gravity (distance) model of house moves fits the data, with around one-third of all house moves within 50km. Most house moves are local. Most, but by no means all. The median move is a little below 100km, the mean 130km. There is a longer tail of long-distance house moves than I would have predicted. 42  Although this may sound simple, it involves a complex matching algorithm to identify housing chains, similar to Chakraborty, Gimpelewicz and Uluc (2017). 31  All speeches are available online at www.bankofengland.co.uk/speeches  31  Chart 19: Distribution of house moves by distance (mortgage-to-mortgage movers in 2018)  Sources: Product Sales Database and Bank calculations. Part of the explanation lies in regional and demographic differences. People outside London and the  South-East – for example, in Scotland – are much more likely to move greater distances (Chart 20). Older people (over 46) are more likely to move larger distances than younger people (under 33) (Chart 21).
Paul Tucker: Remarks on “Making Monetary Policy by Committee” Discussant remarks by Mr Paul Tucker, Executive Director and Member of the Monetary Policy Committee of the Bank of England, on “Making Monetary Policy by Committee” by Alan Blinder, at the Bank of Canada Conference “International experience with the conduct of monetary policy under inflation targeting”, Ottawa, 22-23 July 2008. * * * Central banking involves a lot of learning – by doing, by thinking, researching, and by comparing ourselves with our peers. At the core of that learning process is exchanges amongst central bankers themselves, much of it in Basel. The other rich seam is the academic literature. But relatively few turn (or return) to scholarly reflection after periods of alternatively practising and theorising about central banking. Alan Blinder has therefore provided a signal service, since stepping down as Vice Chairman of the Federal Reserve Board, through his series of papers on monetary policy practice and how it both draws on and fuels theory. Today’s paper, on the role of committees in the making of monetary policy 1, places central banks into categories Blinder first set out a few years ago: single decision taker; autocrat-led college; genuinely-collegial; individualistic. It is especially interesting to the Bank of England, where for just over a decade we have operated a one-member/one-vote system for deciding our policy rate. As Blinder rightly says, comparatively speaking, this is clearly at the ‘individualistic’ end of the spectrum, and is a rare example of the species.

In the interests of effective policy, the Committee as a whole therefore has an interest in setting up some centripetal influences, without making them a binding constraint on individual members. Thus, the publications on the transmission mechanism and on the economic outlook provide a broad, common platform for readers to use when making sense of our individual pronouncements. My hunch is that this gives us greater scope for articulating our individual views without creating misleading impressions. For example, a paper I delivered last year on Money and Credit 4 went into more detail on those parts of the transmission mechanism than any collective statement, or than my colleagues might wish to go. I have found that helpful in recent months, as a few comments on the current conjuncture might illustrate. My take at our recent July meeting was, broadly, that since the May Inflation Report, the near-term outlook for inflation had deteriorated, underlining the risk that the rise in commodity prices will feed through to wage and price setting. The outlook for demand and output had also deteriorated, which in degree should help to contain those upside risks to inflation. Going forward, a key judgment will be whether the prospective slowdown will be sufficient to bring inflation back to target with the current level of Bank Rate, taking into account the tightening in some broader measures of monetary conditions. The final point is what I want to highlight in the context of my remarks today.
What do we know about interactions among the economy’s moving parts? (c)  Movements between regions  In economic systems, interactions occur among all of the factors involved in production and consumption decisions – people, money, goods and services. Capturing flows of these factors, and their interactions, is crucial for understanding how a complex economic system will function. Below I consider flows of money, goods and services. Let me start by considering flows of people. Chart 15 plots migration in and out of various regions in 2016-17, expressed as a proportion of the regional population. Even gross inflows and outflows are relatively modest, varying between 4% (London) and ½% (Northern Ireland). Net flows of people are even more modest, in all cases bar London averaging less than 0.6%. One of the reasons regions are distinct may be because of their ring-fenced populations. 20  Simon (1962). 20  All speeches are available online at www.bankofengland.co.uk/speeches  20  Chart 15: Migration inflows and outflows between different UK regions  Sources: ONS Local Area Migration Indicators and Bank calculations. Notes: Data refer to mid-2016 to mid-2017, as a percentage of 2017 population. Of course, people living in one region can still commute into another for work purposes. Table 1 looks at commuting destinations across UK regions, as a percentage of each region’s population. With the exception of London and the South-East, worker flows from outside of the home region are modest, averaging only 5% of the working population.

Companies’ management information systems can, and are, being used to track flows of workers, goods and services. And administrative data can, and are, being used to track people, money and goods. These micro-level data that could, with time, be pieced together to provide a macro – or micro-to-macro – model of the economy. Or that, at least, is the promise. Managing the Economy  If we can map and model the economy at a high resolution how, if at all, might this affect how economic policy is set? Can analysis of this granular type help when thinking about appropriate forms of policy intervention? Might it help in defining what might be a sensible geographic area for an economic strategy? And might it even help in defining what that economic strategy might be? 34  All speeches are available online at www.bankofengland.co.uk/speeches  34  There is already a deep and rich literature on these topics. One strand looks at optimal currency areas.43 Another looks at optimal fiscal areas.44 And a third looks at optimal political or policy areas.45 This literature identifies a rich range of factors important for determining the optimal spatial dimension of policy. From that long list, let me highlight three factors which are commonly found to play a crucial role:  (a)  Heterogeneity and Specialisation  Other things equal, the greater are the differences in the economic characteristics of an area, the stronger is the case for recognising these differences in the setting of economic policy.
First, conducting monetary policy based on the view that potential is permanently lower – without clear evidence that this is the case – could prove self-fulfilling and costly. The evidence increasingly shows that destroying demand also affects supply. Research on recessions over the last fifty years has found that deep contractions – including those driven by monetary policy – lead to long-lasting effects on real GDP compared to the pre-contraction trend. [20] This suggests that current macroeconomic policies should be designed to avoid unnecessarily heightening the risk that the increasingly likely contraction in coming months becomes a severe and protracted one, which would scar the economy. This requires that energy and fiscal policies remain targeted and contribute to dampen inflationary pressures, helping to keep inflation expectations anchored while preserving productive capacity. But it also requires that monetary policy does not ignore the risks of overtightening. [21] If we were to compress demand in an excessive and persistent manner, we would face the risk of also pushing output permanently below trend, irrespective of whether the initial shocks were temporary or not (that is, even if a harsh policy reaction was unnecessary). And that could not be easily reversed by subsequent policy easing, not least because expansions do not rebuild supply nearly as much as contractions destroy it. [22] Second, even if we were to conclude that supply shocks will lower potential durably, we would still need to examine their effects on demand before deciding our policy stance.

Potential output growth estimates for 2022, 2023 and 2024 in the European Commission’s Autumn 2022 European Economic Forecast also remain higher than the estimates in the Autumn 2019 and 2020 European Economic Forecasts. To put the size of the revisions to potential output in context, the European Commission estimates that potential output was 5% lower 5 years after the onset of the global financial crisis compared to the level it would have had if it had increased each year from 2008 to 2012 at the pre-crisis potential growth rate (that loss increased to more than 9% after 10 years). The European Commission’s Autumn 2022 European Economic Forecast estimates GDP to be 0.2% higher in 2024 than the level it would have had if it had increased each year from 2020 to 2024 at the 2019 potential growth rate, but 0.6 percentage points lower than the level implied by the Autumn 2019 European Economic Forecast. The potential output level in 2024 is therefore not estimated to be significantly different from the level that could be expected before the onset of the pandemic, with the sign of the change depending on the counterfactual used. This may reflect factors that have impacted potential growth in different directions: the pandemic and the recent shocks may have had a negative effect, while Next Generation EU investments and other policy measures in response to the pandemic may have had a positive effect, with the net effect being small. 15.
Less positively, a more difficult economic environment contributes to friction between banks and their customers, for example in the greater incidence of default on debt on the one hand and in the greater tendency among banks, in times of tighter margins, to go after that debt. Whether in good times or bad, a certain volume of complaints is a healthy phenomenon because it encourages improvements in service where complaints are upheld, and improvements in transparency where misunderstandings occur. On a subject so important as the way in which banks handle people's money, there will always be complaints, and we need to continue to develop our machinery for dealing with them. Let me deal quickly with the options identified by the HKMA in its survey last year which, if I read it correctly, the debate within the industry and the community is ruling out. The first option of these is the establishment of a separate banking ombudsman along the lines of the practice in some other jurisdictions. This is, in some senses, a Rolls Royce solution in that it would provide a separate agency, to process and resolve complaints, with powers to arbitrate in complaints and award compensation. It would, however, be a costly solution, and it would take a considerable time to implement. Under such a system, the process of handling complaints would probably also be quite resource-intensive, and it is by no means clear that it would be able to address the full range of complaints being made.

All of these measures have implications for individual customers of banks, but their rationale derives from the MA's principal function: to promote the general stability and effective working of the system. The important thing to note about this "principal function" of the MA under the Banking Ordinance is that it relates to general, "macro", systemic issues, to the safety and soundness of banks and the system as a whole, not to the relationship between individual consumers and their banks. The HKMA's involvement in promoting and encouraging proper standards of conduct and sound and prudent business practices under section 7(2) of the Banking Ordinance is only incidental to its primary function of promoting the stability and effective working of the banking system. Nevertheless, even in the absence of an explicit legal mandate for consumer protection, the HKMA has become increasingly involved in this area, particularly in helping to develop the Code of Banking Practice and in enforcing banks' compliance with the Code. One recent real-life example of this is a quite appalling case of mistaken identity that recently came to our attention. The debt collection agency of a certain bank was pursuing debts against an innocent and entirely unconnected third party who happened to be living in the last known address of the real defaulter. The agent did not identify itself and the bank for whom it was acting when collecting debt.