HICP | Jotup

Clearwater Introduces IRM|Performance to Power Cybersecurity Maturity and Resiliency

Retrieved on:

Tuesday, March 12, 2024

ORLANDO, Fla., March 12, 2024 /PRNewswire-PRWeb/ -- Clearwater, the largest pure-play provider of cybersecurity and compliance solutions for the healthcare industry, announced today at the HIMSS Global Conference & Exposition a new addition to its proprietary SaaS platform, IRM|Pro. The solution, IRM|Performance, is a force-multiplying component of Clearwater's tech-enabled NIST CSF Maturity Assessment and equips healthcare executives with ongoing performance indicators, dashboards, and reporting related to their organization's cybersecurity program performance. IRM|Performacne enables healthcare organizations to measure their conformance relative to the NIST CSF – a healthcare industry standard – and the HHS Voluntary Cybersecurity Performance Goals, published earlier this year.

Key Points:

The solution, IRM|Performance, is a force-multiplying component of Clearwater's tech-enabled NIST CSF Maturity Assessment and equips healthcare executives with ongoing performance indicators, dashboards, and reporting related to their organization's cybersecurity program performance.
Clearwater's IRM|Performance software and NIST CSF Maturity Assessment give healthcare leaders visibility into their current cybersecurity program performance and a means to communicate where they're headed as an organization and what they need to get there.
Designed to empower healthcare organizations to gauge the current state and demonstrate program maturation over time, IRM|Performance and the NIST CSF Maturity Assessment, delivered by Clearwater's dedicated healthcare cybersecurity experts, provide powerful insights into cybersecurity programs and show healthcare leaders a clear path to better cyber resiliency.
IRM|Performance is part of Clearwater's SaaS platform, IRM|Pro, built to help healthcare organizations solve their greatest cybersecurity and compliance challenges.

Philip R. Lane: The economic outlook and monetary policy

Retrieved on:

Wednesday, April 3, 2024

Key Points:

Christine Lagarde: Building confidence in the path ahead

Retrieved on:

Wednesday, April 3, 2024

This box investigates how households have responded to the 2021-23 inflationary episode using evidence from the ECB’s Consumer Expectations Survey.

Key Points:

This box investigates how households have responded to the 2021-23 inflationary episode using evidence from the ECB’s Consumer Expectations Survey.
The findings suggest that households have primarily adjusted their consumption spending to cope with higher inflation.

Debate on: Is the inflation surge over and what are the lessons for monetary policy?

Retrieved on:

Wednesday, April 3, 2024

Consensus, Momentum, Angelini, Tax, MIR, Exercise, Consensus Economics, BIS, DFR, Interest, APP, Labour, Policy, Bank of Greece, PEPP, BSI, ECB, Observation, Aes, Evolution, Refinitiv, Cargo, GDP, T2, Watcher, T3, Deutsche Bundesbank, LHS, Electricity, Projection, MMR, Real, T+2, Disinflation, Bank of France, SMA, Food, OIS, MFI, Perception, CES, Economics, Persistent, Bank for International Settlements, SVAR, Growth, MPE, Common, Consensus decision-making, Bank, XXIV, ILS, HICP, Bloomberg, RHS, BVAR, Elasticity, Unit, Lombard, Surface finishing

Shocks to the shortages variable are constructed as deviations in the values from the sample mean.

Key Points:

Shocks to the shortages variable are constructed as deviations in the values from the sample mean.
Shocks to the vacancy-to-unemployment ratio (labour market variable) are constructed
as the actual value minus the value in the fourth quarter of 2019.
?Indirect impact of energy prices on non-energy inflation? is the sum of the indirect effects of oil,
gas and electricity prices.
3
Historical
Rubric comparison of inflation episodes in the euro area ? headline and core
Headline

Core

(percentage points)

(percentage points)
Current euro area episode
Past global episodes

Current euro area episode
Past global episodes
2

2

0

0

-2
-4

-2

-6
-8

-4

-10
-12

-24

-18

-12

-6

0

6

12

18

-6

24

Months around inflation peak

-24

-18

-12
-6
0
6
12
Months around inflation peak

18

Sources: BIS, Eurostat and ECB calculations.
The dark blue line represents the latest developments in headline and core inflation for the euro area, relative to the October
2022 peak.
Non-energy industrial goods inflation refers to a panel of all euro area countries, while services inflation refers to
a panel of 30 AEs and 28 EMEs.
Month = 0 is when the headline inflation value is at the highest during that particular episode.
The dark blue line represents the latest developments
in non-energy industrial goods and services inflation for the euro area, relative to the October 2022 peak.
unprocessed
food and energy
HICPX

8
3.0

3.0

2.5

2.5

2.0

2.0
1.5

1.5
1.0
Feb-24

Jul-24

1.0
Dec-24 Feb-24

Jul-24

8

7

7

6

6

5

5

4

4

3

3

2

2

1

1

Adjusted
measures

Difference
4

3

2

1

0
0
0
Feb-24 Jan-23 Jul-23 Jan-24
Jan-23 Jul-23 Jan-24
Feb-24 Jan-23 Jul-23 Jan-24
Feb-24

Dec-24

Sources: Eurostat, March 2024 ECB staff short-term inflation outlook, Consensus
Economics, Bloomberg and ECB calculations.
The ?adjusted?
measures abstract from energy and supply-bottleneck shocks using a large SVAR, see
Ba?bura, Bobeica and Mart?nez-Hern?ndez (2023), ?What drives core inflation?
Notes: 5-days moving average risk-neutral
probabilities of inflation implied by five-year and tenyear zero-coupon inflation options.
16
8

12
Quarters

16

20

Policy
Rubriccounterfactuals
Interest rate under alternative
counterfactuals

Counterfactual impacts on
Inflation

(percentages per annum)

(annual percentage change)

Baseline
Earlier and longer
Earlier, longer and higher

8

Baseline

7
6
5
4
3
2
1
0
-1
2021Q4

2022Q4

2023Q4

2024Q4

Earlier, longer and higher

10

2

8

0

6

-2

4

-4

2

-6

0

-8

-2

2025Q4

Earlier and longer

Output gap

(p.p.
The RHS chart displays the impact on inflation (first panel) and output gap (second panel) for each of the hypothetical alternative paths of the interest
rate.
As a caveat, financial feedback loops as well as feedback loops between inflation expectations and inflation are not activated.

Piero Cipollone: The confidence to act: monetary policy and the role of wages during the disinflation process

Retrieved on:

Wednesday, April 3, 2024

This box investigates how households have responded to the 2021-23 inflationary episode using evidence from the ECB’s Consumer Expectations Survey.

Key Points:

This box investigates how households have responded to the 2021-23 inflationary episode using evidence from the ECB’s Consumer Expectations Survey.
The findings suggest that households have primarily adjusted their consumption spending to cope with higher inflation.

Consumer participation in the credit market during the COVID-19 pandemic and beyond

Retrieved on:

Tuesday, April 2, 2024

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We find that credit demand is highest when

Key Points:

We find that credit demand is highest when
the first lockdown ends and it drops when supportive monetary compensation schemes are implemented.
Credit is more likely to be
accepted under favourable borrowing conditions and after the approval of national recovery plans.
We also find
that demographic, economic factors, perceptions and expectations are associated with the demand for credit and
the credit grant.
First, it adds to a rapidly growing literature on household
borrowing behaviour during the COVID-19 pandemic; see, for example, Ho et al.
We provide evidence that credit applications and credit acceptances display a different pattern over
time.
Credit is more likely to be accepted under favourable borrowing conditions and after the
approval of national recovery plans.
In almost all countries
households are significantly less likely to apply and to get their credit approved than in Germany.
In line with literature, we show that
demographic and economic factors affect the probability for credit applications and credit approval.
In addition,
the paper shows that consumer perceptions and expectations matter when they decide to apply for credit.
Introduction
The participation of households in the credit market receives wide attention in the consumer finance literature
because consumer credit enters the monetary policy transmission mechanism through the so-called ?credit
channel?: changes in credit demand and supply have an effect on consumers' spending and investment, which in
turn affect economic growth.
We use microdata from the ECB?s Consumer Expectations Survey (hereinafter CES), a survey that
measures consumer expectations and behaviour in the euro area.
Its panel dimension allows for an assessment of
how consumer behaviour changes over time and how consumers respond to critical economic shocks.
This way we can gauge how credit applications and credit acceptances change under different, almost
opposite, borrowing conditions.
We also distinguish between the demand for long-term secured loans (mortgages) and for short-term
uncollateralized loans (consumer loans).
ECB Working Paper Series No 2922
3

We use probit models to estimate the probability of the consumer to apply for credit and the credit being granted.
The rate peaks in 2020Q3 which reflects the rebound in the demand for loans when the first lockdown ended.
In almost all countries households are significantly less likely
to apply and to get their credit approved than in Germany.
However,
when it comes to credit acceptance, we observe that the two groups of households are more similar.
Finally, we find some heterogeneity with respect to the type of credit, particularly between secured and unsecured
debt.
The demand for
consumer credit is insignificant for liquid households and decreases significantly for constrained households in
the last two quarters of our timespan.
The first consists of a recently growing literature which
explores consumer behaviour in the credit market during the COVID-19 pandemic, mostly in the United States.
Sandler and Ricks (2020) show that consumers did not use credit card debt for financial liquidity in the early stage
of the COVID-19 pandemic.
(2020) report that credit card applications and new mortgage loans
declined during the first months of the pandemic in regions with more unemployment insurance claims.
Lu and
Van der Klaauw (2021) show that there was a sharp drop in consumer credit demand, especially for credit cards.
(2022) document that there was a substantial decrease in the usage of credit cards and home equity lines
of credit by Canadian consumers.
Our paper is also consonant with studies on the association between financial and demographic factors and
consumers? participation in the credit market as well as on the demand for specific types of credit.
January 2020 ? October 2020 - The two main events are the outbreak of the COVID-19 pandemic and the
consequential lockdowns in the euro area.
4 If the
respondent has applied for more than one type of credit, she is asked to refer to the most recent credit application.
Between 2021Q3 and 2022Q3 the acceptance
rate stays above the average values, mirroring the easing of credit standards for consumer credit and other lending
to households during this period.
Second, we can investigate the presence of nonlinearities in how liquidity and the credit type interact in explaining credit applications.
(2023) ? who show that in the United States the local pandemic severity had a strong
negative effect on credit card spending early in the pandemic, which diminished over time.
First, we select mortgages and consumer credit as the two mostly reported categories for secured and
13

The full estimation results are reported in Table 3.
The right-hand side panel of Figure 6 shows that the demand for consumer credit is insignificant for both liquid
and illiquid households.
It also shows that
subjective perceptions of credit access, financial concerns and expectations on interest rates matter for the demand
for credit.
In Bertola, G., Disney
R., and Grant, C. (eds) The Economics of Consumer Credit, Cambridge MA, MIT Press.
Horvath, A., Kay, B. and Wix, C. (2023) The COVID-19 shock and consumer credit: Evidence from credit card
data.
Magri, S. (2007) Italian households? debt: The participation to the debt market and the size of the loan.

The unequal impact of the 2021-22 inflation surge on euro area households

Retrieved on:

Tuesday, April 2, 2024

The 2021-22 surprise inflation surge had a major impact on households in the euro area.

Key Points:

The 2021-22 surprise inflation surge had a major impact on households in the euro area.
Indeed, not everyone was a net loser: while about 70% of households suffered a loss, the rest enjoyed moderate gains.

Measuring market-based core inflation expectations

Retrieved on:

Thursday, February 15, 2024

Abstract

Key Points:

Abstract
We build a novel term structure model for pricing synthetic euro area core inflation-linked
swaps, a hypothetical swap contract indexed to core inflation.
The model provides estimates of market-based expectations for core inflation, as
well as core inflation risk premia, at daily frequency, whereas core inflation expectations from
surveys or macroeconomic projections are typically only available monthly or quarterly.
We
find that core inflation-linked swap rates are generally less volatile than headline inflationlinked swap rates and that market participants expected core inflation to be substantially
more persistent than headline inflation following the 2022 energy price spike.
In this paper, we aim to infer market-based core inflation expectations, which are otherwise
not directly observable because no financial asset directly tied to core inflation exists.
We deem this second assumption reasonable because HICP inflation itself is a linear combination
of core as well as energy and food inflation.
The level of 2 percent and relatively low volatility of
long-term inflation expectations suggests that inflation expectations are firmly anchored at the
ECB?s 2 percent inflation target.
This assumption appears reasonably uncontroversial,
as core inflation is a sub-component of headline inflation, which the observable headline ILS
rates are tied to.
Our estimates of core ILS rates reflect both market participants? genuine core
inflation expectations and a core inflation risk premium, but our model explicitly allows for
this decomposition.
The model-implied estimates of core ILS rates appear reasonable along several dimensions:
(i) like realized core inflation is less volatile than headline inflation, the core ILS rates are less
volatile than headline ILS rates, (ii) core ILS rates comove less with oil prices than headline
ILS rates, (iii) the core inflation expectations, as reflected in core ILS rates, typically evolve
similarly as the core inflation projections by Eurosystem staff, and (iv) consistent with market
commentary at the time, core ILS rates suggest that market participants expected core inflation
to be substantially more persistent than headline inflation following the 2022 energy price spike.
To the best of our knowledge, we are the first to price core ILS rates and decompose them into
market-based expectations for and risks around the core inflation outlook.
Our approach to inferring core ILS
rates from headline ILS rates, realized headline and core inflation as well as survey expectations
for headline and core inflation is also related to Ang et al.
Relative
to their study, we separately measure core inflation expectations and risk premia, we provide
core inflation expectations at a higher-frequency, and we provide evidence on the causal effects
ECB Working Paper Series No 2908

6

of monetary policy shocks on core inflation expectations and risk premia.
Specifically, we decompose the synthetic core ILS rates
into average expected core inflation over the lifetime of the swap contract and a core inflation
risk premium that compensates investors for core inflation risk.
In
our model below, this term is constant over time and relatively small, so we will simply refer
to the core inflation risk premium as the difference between the core ILS rate and the average
expected core inflation over the lifetime of the swap contract.
3.2
Core ILS rates

To have a joint model for headline and core ILS rates, we need one further assumption on the
dynamics of realized core inflation.
The assumption that core inflation is driven by the same set of factors as headline inflation
should be relatively uncontroversial: since headline inflation is a weighted average of core and
food and energy inflation, it should reflect any factors driving core inflation.
If there are factors
driving food and energy inflation, which do not show up in core inflation, then those factors
should still show up in headline inflation.
In step two, to be able to infer the factor
loadings of core inflation, we would regress realized core inflation onto the estimated latent
factors to identify the additional parameters in equation (12).
Before the fourth
quarter of 2016, the SPF did not ask respondents for their core inflation expectations, so we
are not able to use survey-based information about core inflation before then.
Before
2016, the fitted core inflation series is somewhat above the realized one, potentially reflecting
that the model has limited information about core inflation over this early period due to the
lack of information about core inflation from surveys.
This could have been the
case if one of the factors moved core inflation and energy and food inflation in exactly offsetting
direction, so the overall impact on headline inflation was exactly zero.
During 2021, for example, there were
ECB Working Paper Series No 2908

25

Figure 7: Decomposition of synthetic core ILS rates
2y core ILS

5y core ILS

5
4

5
ILS

premia

exp

4

ILS

premia

exp

3

3

2

2

1

1

0

0

-1

-1

-2
2017 2018 2019 2020 2021 2022 2023

-2
2017 2018 2019 2020 2021 2022 2023

10y core ILS

5y5y core ILS

5
4

5
ILS

premia

exp

4

ILS

premia

exp

3

3

2

2

1

1

0

0

-1

-1

-2
2017 2018 2019 2020 2021 2022 2023

-2
2017 2018 2019 2020 2021 2022 2023

Note: Synthetic core ILS rates decomposed into genuine core inflation expectations and core inflation risk
premia.
ECB Working Paper Series No 2908
26

Figure 8: Decomposition of ILS rates
2y ILS

5y ILS

5
4

5
ILS

premia

exp

4

3

3

2

2

1

1

0

0

-1

-1

-2
2006

2010

2014

2018

2022

-2
2006

ILS

2010

10y ILS

2018

2022

5
ILS

premia

exp

4

3

3

2

2

1

1

0

0

-1

-1

-2
2006

2014

exp

5y5y ILS

5
4

premia

2010

2014

2018

2022

-2
2006

ILS

2010

premia

2014

2018

exp

2022

Note: ILS rates decomposed into genuine core inflation expectations and core inflation risk premia.
We find that the headline inflation risk premium
indeed does responds more strongly than the core inflation risk premium.
The key
assumption underlying our approach is that traded headline ILS rates span core inflation, which
ECB Working Paper Series No 2908

35

should be reasonably uncontroversial as core inflation is a sub-component of headline inflation.
We fit the model to euro area headline ILS rates, realized headline and core inflation, and
both headline and core inflation expectations reported in the SPF.
Decomposing our core ILS rates into genuine core inflation expectations and core
inflation risk premia shows that shorter maturities mainly reflect core inflation expectations,
while the core inflation risk premium matters relatively more for longer maturities.
Our results suggest that a monetary policy tightening surprise significantly lowers
near-term core inflation expectations, although less so than it lowers headline inflation expectations.

Gas price shocks and euro area inflation

Retrieved on:

Tuesday, February 13, 2024

Transfer, Person, Marques, OPEC, Interval (mathematics), Policy, NBER, Research Papers in Economics, The Economic Journal, Danmarks Nationalbank, Socialism, Energy transition, VIX, Canadian International Council, Paper, E30, Great, Macroeconomics, VAR, Central bank, Balke, Quarterly Journal, Q43, Census, Elasticity, USD, Projection, PMI, Social science, Hou, Bank of France, Topa, Fertilizer, Electricity, SSRN, University, A.5, Section 2, Natural gas, COVID-19, Swings, Overalls, Rotation, Journal of Monetary Economics, Harmonization, Title Transfer Facility, Pain, Ferrari, Uncertainty, Statistics, Medical classification, C50, Harper (publisher), Democracy, Shock, IMF, TTF, Fed, PPI, Power, European Central Bank, Monetary economics, Temperature, Section 3, E31, Nature, Food, Local, Joseph Schumpeter, Website, Energy economics, Speech, DeSantis, GDP, Rigidity, BVAR, Confidence interval, Money, Refinitiv, Bank, Baumeister, Pressure, Oil, Deutsche Bundesbank, International Energy Agency, Employment, Section 4, GIZ, C54, Sun, ECB, European Economic Association, Weather, A.9, Quarterly Journal of Economics, Exercise, HICP, Technical report, Attention, Literature, Journal of Applied Econometrics, Reproduction, International economics, Political economy, Absorption, Joseph Stiglitz, Unemployment, Journal, American Economic Review, Index, Section 5, Business, IP, Bachmann, Research, Federal Reserve Bank, Government, PDF, IWH, Complexity, Failure, Energy Information Administration, Explosive

We document

Key Points:

We document
how gas price fluctuations have a heterogeneous pass-through to euro area prices
depending on the underlying shock driving them.
How do gas price shocks feed through to euro area
inflation, and is the pass-through shock-dependent?
We analyse the importance of gas price shocks
for euro area inflation in two steps.
We identify three structural shocks driving European gas prices,
inspired by the literature on oil but tailored to the European gas market: (i) a gas supply
shock, which reduces the supply of natural gas to the European market, increases the
gas price and lowers gas inventories; (ii) an economic activity shock, which lifts demand
for gas due to higher economic production, and finally (iii) a shock to gas inventories,
when gas prices are driven by precautionary demand by gas companies.
First, all three identified shocks are
important drivers of gas price dynamics, but they differ in how persistently they push
ECB Working Paper Series No 2905

2

up gas prices.
The effect on euro area HICP of a shock to gas supply is more
persistent and somewhat higher than when gas prices are driven by economic activity
shocks.
A final key finding is that the pass-through of gas market shocks to euro area inflation
appears non-linear.
The unprecedented volatility of gas prices
contributed to the inflation problem in the euro area, with the gas price shocks feeding
through producer prices, wages and persistently lifting core inflation.
More expensive
energy contributed substantially to the rise in inflation in Europe during 2022.2
Figure 1: Gas price and euro area Harmonized Index of Consumer Prices.
How do gas price shocks feed through to euro area
inflation, and is the pass-through shock-dependent?
For instance, about 75% of gas imports to the euro area arrives
through pipelines, making gas imports difficult to substitute and gas markets subject to
3
See for example the evidence by Rubaszek and Uddin (2020) for the US economy.
We analyse the importance of gas price shocks for
euro area inflation in two steps.
We identify three structural shocks driving European gas prices,
inspired by the literature on oil but tailored to the European gas market: (i) a gas supply
shock, which reduces the supply of natural gas to the European market, increases the
gas price and lowers gas inventories; (ii) an economic activity shock, which lifts demand
for gas due to higher economic production, and finally (iii) a shock to gas inventories,
when gas prices are driven by precautionary demand by gas companies.
First, all three identified shocks are
important drivers of gas price dynamics, but they differ in how persistently they push
up gas prices.
But when gas prices are driven by
inventory demand shocks, the price effect typically dies out within one quarter.
A final key finding is that the pass-through of gas market shocks to euro area inflation appears non-linear.
The unprecedented volatility of gas prices
contributed to the inflation problem in the euro area, with the gas price shocks feeding
through producer prices, wages and persistently lifting core inflation.
(2022) and Alessandri and Gazzani (2023) identify gas supply shocks using VAR models,
finding that gas price shocks lead to persistent increases in headline inflation.14 Ba?bura
et al.
(2023) find positive effects of gas price shocks on core inflation in a BVAR for
the euro area that includes one type of gas shock along a longer list of macroeconomic
shocks.
3.1
Data

For the gas market BVAR model, we use gas quantities, gas prices, gas inventories and
euro area industrial production, as displayed in Figure 2.
(2015) to optimize
ECB Working Paper Series No 2905

13

the posterior distribution.16 The vector Y includes the European gas quantity proxy, gas
inventories, the European gas price benchmark and euro area industrial production.
As demand for gas increases, the gas price also rises
while inventories fall as agents use gas in storage to partially satisfy higher demand.
Shocks to gas
quantities driven by gas supply or inventory shocks tend to revert to pre-shock levels after
around five to seven months, while economic activity shocks lead to a more long-lived
increase in gas demand.19 Dynamics in gas inventories are more similar across shocks.
3.4
Historical events in the European gas market

Before analysing the transmission of the different types of gas shocks to euro area prices,
we show how the model interprets the unprecedented gas price rise in 2022 in terms of
driving factors, and compare it with previous historical episodes of heightened gas price
volatility as a way of validating the model.
Inventory shocks play a
slightly smaller role, accounting for 17% of gas quantity and 23% of gas price fluctuations
while the residual component (i.e.
4
Pass-through of gas price shocks to consumer prices

The pass-through of gas price shocks to inflation is likely to be multi-faceted.
We first consider four outcome variables y: the European gas price, euro area HICP,
core HICP and energy HICP.
Third, depending on the driving factor, gas price increases can pass through to core
inflation in the euro area.
The results underline that gas price shocks can have important implications for inflation in the euro area ? depending on the driving factor of higher gas prices.
Casoli, C., Manera, M., and Valenti, D. ?Energy shocks in the euro area: disentangling
the pass-through from oil and gas prices to inflation?.

A forward-looking tracker of negotiated wages in the euro area

Retrieved on:

Saturday, February 10, 2024

Online, Blog, Country, Monetary Policy Committee, Deutsche Bundesbank, The, Bank of Greece, Bank, Statistics, Growth, No-no, GDP, Working Group, Projection, Calendar, Curve, Database, Selection bias, Trinity College, CPH, Lecture, RHS, MPC, Inflation, Food, Unemployment, Private sector, Journal, National Bank of Belgium, CPE, BDF, WGF, Eurostat, Social science, JEL, WT, Statistics Austria, Central bank, Forward, COVID-19, Labour, Government, Exercise, Social Security, Bank of France, Labour economics, NCBS, HICP, JRS, Bank of Slovenia, ULC, Letter, PDF, Bank of Lithuania, SSRN, Social, Work, COE, ECB, Research Papers in Economics, Data, Central Bank of Cyprus, Cross, Phillips curve, Employment, Forecasting, Welfare, Structure, Collective bargaining, Bias, Bank of Italy, De Nederlandsche Bank, Green, Rotation, Rigidity, School, Nationalbank, Section 5, European Central Bank, Reproduction, J50, Comment, NMW, Ministry of Labour, Index, Central Bank of Ireland, Research, E24, ISSN, Public sector, Limited, Chart, Education, Policy, Ministry, Banco de Portugal, Trinity College Dublin, Section 3, Disinflation, CBS, CBI, Coronavirus, Acceleration, National bank, Frankfurt, Bank of Finland, MPE, Section 4, Annual, OECD, Nickel, Clothing

Key Points: