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Drivers of underlying inflation in the euro area over time: a Phillips curve perspective
1 Motivation and overview
Box 1 Other countries' experiences with Phillips curves
2 Phillips curve models for euro area underlying inflation: what are the choices?
Box 2 Linear and non-linear Phillips curves
3 The drivers of euro area underlying inflation implied by Phillips curve models
Prepared by Elena Bobeica and Andrej Sokol
Published as part of the ECB Economic Bulletin, Issue 4/2019.
In this article we review the evolution of euro area HICP inflation excluding energy and food since the Great Financial Crisis through the lens of the Phillips curve. This period is particularly interesting, as the euro area experienced two recessions (in 2008-2009 and 2011-2014) and a protracted episode of low inflation from 2013 onwards. We estimate a large set of Phillips curve models for the euro area and review the interpretation of inflation developments that they provide over time. We find that our models can account for much of the weakness in underlying inflation between 2013 and mid-2017, but that they cannot account for the weakness in underlying inflation towards the end of our sample.
The decade since the onset of the Great Financial Crisis in 2008 is known for a "twin puzzle" in inflation developments across advanced economies. The first years following the crisis are associated with a missing disinflation episode, as inflation appeared to fall by less than the ensuing recessions would have led us to expect.[1] More recently, as most economies gradually recovered, economists have puzzled over missing inflation,[2] with the latter episode being much more prolonged. Taking averages since the launch of the euro as benchmarks, in the euro area both headline HICP inflation and HICP inflation excluding energy and food (HICPX, henceforth "underlying inflation") dropped below their respective averages after 2009 (see Chart 1), but the missing disinflation view would have predicted an even more marked fall. After a short-lived recovery, inflation rates again fell from 2013 onwards, initiating a protracted period of below-average inflation, which in the case of underlying inflation persists to the present day. The missing inflation view finds the latter episode hard to square with a gradual recovery in economic activity in the euro area that has brought the unemployment rate back to pre-crisis levels (see Chart 2).
HICP inflation and HICP inflation excluding energy and food in the euro area
(annual percentage changes)
Sources: Eurostat and ECB calculations.
Note: The dotted lines represent historical averages since 1999.
HICP inflation excluding energy and food and the unemployment rate in the euro area
(annual percentage changes (right-hand scale), percentages (left-hand scale, inverted))
Source: Eurostat.
Both academics and practitioners use versions of the Phillips curve to understand and communicate inflation developments. In the broadest sense, the Phillips curve is an expression of the notion in economic theory that economic activity, and more precisely the degree of excess demand or supply, should have a bearing on price and inflation developments. The relationship is grounded in many popular economic theories, such as the New Keynesian framework, where inflation is primarily linked to firms' marginal costs (often proxied with a measure of economic slack) and forward-looking inflation expectations. Phillips curves have long enjoyed great popularity as an empirical tool, but for that very reason the missing disinflation and missing inflation episodes have stirred intense debates about the relationship, including whether it is alive or dead (i.e. steep or flat), and linear or non-linear.
Attempts to simply link the behaviour of inflation to the level of economic activity raise some important questions. For instance, a naïve look at the stability of such a relationship (see Chart 3) would suggest that, compared with the pre-crisis period, the link between real activity and inflation might have "flattened" in the following period, which includes the two puzzling episodes. But many economic factors can shift the level of inflation for a given amount of economic slack, blurring the underlying economic relationship when viewed in a scatterplot. For example, inflation expectations and the cost of imported inputs are important elements of price-setting decisions, and their changes can lead to shifts in the Phillips curve relationship without necessarily changing its slope. On the other hand, the behaviour of economic agents could change over time, for example depending on whether the economy is in recession or not, meaning that the slope could vary over different periods. Without appropriately taking into account such considerations, there is a risk of drawing the wrong conclusions about the strength of the link between inflation and economic activity.
HICPX inflation and the unemployment rate in the euro area
(x-axis: percentages; y-axis: annual percentage changes)
Note: Linear regression lines for the two samples are shown in grey.
The ECB has also relied on Phillips curve models to understand and communicate inflation developments since the Great Financial Crisis. The Phillips curve is an intuitive yet powerful way of conveying the link between inflation and economic activity, which lies at the heart of monetary policy. Thus, as in other central banks and policy institutions (see Box 1 for some case studies), Phillips curves are one element of the analytical toolkit routinely deployed by the ECB to analyse and communicate inflation (and wage growth)[3] developments. Reduced-form estimates of this relationship remain popular due to their simplicity and transparency. However, they require regular review and scrutiny in order to remain useful for analytical, decision-making and communication purposes. This includes all the important choices that have to be made for their empirical set-up: for instance, whether to focus on headline inflation, which is more exposed to commodity prices and other external shocks, or on measures of underlying inflation; what is the most appropriate measure of economic activity to use; what other global and/or domestic drivers of inflation besides economy activity should be included; and whether the relationship should be allowed to change in more complex ways, for example depending on the stage of the economic cycle. Section 2 and Box 2 focus on some of these important issues. In Section 3, we then revisit the recent history of inflation in the euro area through the lens of a large set of reduced-form Phillips curve models, and find that estimated Phillips curves can account for much of the weakness in underlying inflation since 2013, imputing the bulk of it to its key determinants, except for the last few outturns, which cannot be explained well by our models.
Other countries' experiences with Phillips curves
Prepared by Alexander Al-Haschimi
Major central banks use the Phillips curve to assess and communicate inflation developments. For instance, the Federal Reserve System tracks closely how well Phillips curves estimated using a variety of approaches can explain data on the US economy.[4] Some results suggest that in the United States, the link between unemployment and inflation has weakened over time. Indeed, in recent years the United States has been experiencing both low unemployment and low inflation concurrently, which is consistent with a flatter Phillips curve. Federal Reserve Chair Jerome Powell has argued that a number of factors have weakened the effect of labour market tightness on inflation.[5] One factor cited was a more effective conduct of monetary policy, resulting in a stronger anchoring of inflation expectations. Other factors potentially relate to the internationalisation of production structures and the higher import content of goods consumed, which give exchange rates and global prices a greater role in price determination.[6]
A related question, particularly relevant given the very tight labour markets in some advanced economies, including the United States and Japan, is to what extent the Phillips curve is non-linear. In his remarks at the 2019 US Monetary Policy Forum, John Williams also discussed the possibility that the employment-inflation relationship becomes strong only when unemployment is very low, as suggested by Hooper, Mishkin and Sufi (2019).[7] This finding would be highly policy-relevant, as it suggests that while thus far a tight labour market has co-existed with low inflation, a further tightening in the US labour market may lead to inflation rising above target. Williams pointed out that the results for this type of non-linearity in the Phillips curve are often not robust, but their existence would significantly alter the policy trade-offs a central bank is facing.[8]
In Japan, the linearity of the Phillips curve has also been questioned.[9] Japan has also been experiencing a tight labour market and low inflation, which could be an indication of a flatter Phillips curve. There are a number of potential explanations for why the country's low unemployment rate does not feed through more strongly to wage and price inflation. Some factors cited are structural, and relate in part to worker preferences for employment stability over wage increases, as well as hidden labour market slack arising from involuntary part-time workers who are not fully captured by the unemployment rate. However, as in the United States, there is a debate as to when the low and falling unemployment rate should lead to stronger increases in wages and prices. Harada (2018) recently discussed this issue within a Phillips curve framework. He showed estimates suggesting that inflation becomes more responsive to the labour market when the unemployment rate falls below 3%, and concluded that this could imply that the unemployment rate needed to decline further for inflation to reach its target of 2% (see Chart A).[10]
Chart A
Phillips curve for Japan
Sources: Japanese Ministry of Internal Affairs and Communications and Haver Analytics.
Notes: Core inflation in year-on-year percentage changes, measured as the consumer price index for all items excluding fresh food, non-alcoholic beverages, and energy and adjusted for changes in consumption tax. "Abenomics" refers to the economic policies of Japanese Prime Minister Shinzō Abe.
We follow a "thick modelling" approach and bring a large number of reduced-form single-equation Phillips curve models to the data. As emphasised in ECB (2014),[11] there are countless – similarly plausible – empirical specifications of the Phillips curve, reflecting various choices, such as the variables to be included, the functional form and the estimation strategy. One way to mitigate some of this model uncertainty is to choose a generic specification, and estimate different versions of it, changing how we measure each variable – an approach referred to as "thick modelling".[12] The general specification is the following:
πt=c+γ×πt-1+α×πte+β×xt-1+γ×Zt-l+εt
where πt is inflation, πte is a measure of inflation expectations, xt is a measure of economic activity or "slack" and Zt-l captures external price shocks, which in some specifications are allowed to enter the equation with a longer lag l to allow for a slower pass-through to domestic prices. The choice of functional form and estimation strategy addresses tractability and simplicity concerns, but also reflects the proven ability of such models to fit euro area data reasonably well.[13] Effectively, the model is an empirical version of a hybrid New Keynesian Phillips curve, where inflation is driven by forward-looking inflation expectations (proxied here by survey measures), past inflation is allowed to play a role as well (to capture backward-looking expectations and other sources of persistence in price setting) and firms' marginal costs are proxied by measures of slack or economic activity. External variables are included to control for an important source of supply-side shocks. Figure 1 offers a synopsis of the main specification choices, without aiming to be exhaustive on all possible counts.
Stylised decision tree for the specification of a reduced-form Phillips curve model
Source: ECB.
While the objective of the ECB is unambiguously defined in terms of headline HICP inflation, in this article we focus on measures of underlying inflation, which are less volatile and can help to identify and illustrate the key drivers of price developments (see Figure 1, panel A). Developments in total consumer price index (CPI) inflation may be temporarily influenced by factors that are of a short-term nature, such as swings in commodity prices. In order to focus on the more persistent factors driving inflation, in many empirical applications of the Phillips curve model (and beyond), underlying inflation measures are used instead. However, there are many available measures of underlying inflation. Popular choices include: permanent exclusion measures (such as HICP inflation excluding energy and food), temporary exclusion measures and model-based measures.[14]
We use several measures of economic slack or activity to capture the impact of firms' costs on inflation (see Figure 1, panel B).[15] Most empirical approaches assume that marginal costs are proportional to economic slack,[16] proxied by the output gap or the unemployment gap. Such unobservable gaps can be obtained by applying statistical filtering techniques, via estimates of potential output based on a production function (e.g. OECD or IMF methodologies), or endogenously, in a manner consistent with inflation developments, as in Blanchard et al. (2015), Jarociński and Lenza (2018) and Chan et al. (2016).[17] Using multiple measures is one way of mitigating the model uncertainty inevitably surrounding estimates of economic slack. Another approach is to directly use observable measures of economic activity, such as the unemployment rate or GDP growth, which, however, has the significant downside of blurring demand and supply factors. More recently, several studies have recommended using the short-term unemployment rate or gap instead of total unemployment measures.[18] Regardless of the reference measure, additional complications arise from estimating slack in real time, partly related to the potentially large revisions to some of the macro data used to proxy slack.[19]
We use available survey measures to proxy inflation expectations (see Figure 1, panel C).[20] The inflation expectations of firms and workers/consumers are not available for most countries, so several strategies have been adopted to address the issue. Backward-looking expectations, i.e. assuming that they are based on past inflation, are the simplest one, and the inclusion of a lagged inflation term in equation (1) is partly motivated by this. To measure forward-looking expectations, survey measures are a convenient way to proxy the beliefs of economic agents regarding future price movements. Their main caveat is that such surveys usually reflect expectations of professional forecasters, which could differ markedly from those of price setters or consumers.[21]
We also control for external supply-side shocks that might hit domestic prices (see Figure 1, panel D).[22] In an increasingly globalised world, both domestic headline and underlying inflation can be sensitive to various external supply-side shocks, such as those coming from commodity and other import prices. There is some empirical evidence for the United States and other countries that import prices do affect inflation in a Phillips curve framework.[23] On the other hand, there is less empirical support when it comes to an independent influence of the global business cycle on domestic inflation.[24]
The relevant variables to include are not the only source of uncertainty in the Phillips curve; the functional form matters as well. The choice of specification is often driven by the scope and purpose of the analysis; for example, if a linear specification turns out not to offer a satisfactory explanation of outcomes, non-linear specifications can be deployed. Box 2 discusses some important departures from the linear benchmark model in equation (1) in the context of recent ECB work on Phillips curves.
We estimate 550 versions of the baseline model and find the euro area Phillips curve to be alive, but we also find evidence pointing to the importance of inflation drivers other than domestic real activity. Estimation results point to a statistically significant and economically plausible link between euro area inflation and its key drivers. Focusing on the relationship with real activity, Chart 4 shows the Phillips curve slope across specifications for each measure of slack or economic activity. In virtually all 550 models under review, the real activity measure is statistically significant with the theoretically implied sign, confirming the visual impression given in Chart 2 regarding the co-movement between underlying inflation and economic activity in the euro area. However, the slope is generally not very steep and the coefficients of other relevant drivers, such as inertia, expectations and external shocks, are often also significant, pointing to the importance of factors beyond slack for adequately explaining inflation developments. In other words, not only movements along the Phillips curve, but also shifts in the curve, need to be taken into account.
Estimated Phillips curve slope across all specifications
(regression coefficients on standardised measures of economic slack/tightness)
Sources: European Commission, ECB, Eurostat, IMF, OECD and ECB calculations.
Notes: We consider the following measures of slack: (1) output gap – model-based estimate; (2) output gap – IMF; (3) output gap – European Commission; (4) output gap – OECD; (5) unemployment rate; (6) unemployment gap – model-based estimate; (7) unemployment gap – IMF; (8) unemployment gap – European Commission; (9) unemployment gap – OECD; (10) short-term unemployment rate; (11) the U6 measure. The unemployment rates/gaps have been inverted. Sample: Q1 1995 to Q3 2018. All measures of slack/tightness are standardised for the coefficients to be comparable across specifications. The vertical bars show the range of coefficients across all specifications including a particular measure of economic slack/tightness or activity.
Linear and non-linear Phillips curves
Prepared by Andrej Sokol
Empirical Phillips curve models are often linear. Equation (1) in Section 2 is a fairly standard specification of a single-equation linear Phillips curve, where lagged inflation, a measure of slack, a measure of inflation expectations and a measure of import prices are included. Linearity refers both to linearity of the parameters (the right-hand-side term is a linear function) and of the variables (i.e. variables enter the equation with the units they are measured in). Both assumptions can be relaxed in a number of ways.
There are several possible non-linear specifications of the Phillips curve. The most common forms of non-linearity include transformations of the independent variables, such as square (or even higher-order) slack terms, which can introduce both convexity and concavity in Phillips curves. Similar and more sophisticated relationships can be fitted by weighting the slack measure with another variable that captures the state of the economy; for example, a simple dummy variable can achieve several forms of "piecewise linearity", which can approximate different regimes, such as booms and deep recessions, as opposed to "normal times". More sophisticated devices, such as non-linear splines or Markov switching, are sometimes also used in the estimation of non-linear Phillips curves.[25]
Behind the notion of a non-linear Phillips curve often lies the idea that pricing behaviour could be different at different stages of the economic cycle. This in turn might be due to psychological, institutional or technological considerations and their interplay in a modern market economy. One argument with a long history relates to downward nominal wage rigidities; i.e. workers being reluctant to accept (or firms to impose) cuts in nominal wages in a downturn. This could be due to collective bargaining arrangements, or a psychological reluctance to see one's pay cut in nominal terms. The implication is that in the presence of a large amount of economic slack, wages (and therefore prices) will change at a different rate than during more normal periods, thus potentially bending the Phillips curve into a more convex shape. A similar phenomenon can occur if firms experience short-run capacity constraints that make it difficult to immediately satisfy further increases in demand. One example would be mothballed equipment that can only be put back into use with a time lag and at some cost. In such a situation, firms might increase prices before increasing their capacity to fully satisfy the additional demand, whereas in more normal times they would adjust inputs to production first, thus again making the Phillips curve more convex. Another source of convexity is the idea that price changes could be more frequent in periods of high inflation.
Some theories predict a concave rather than a convex Phillips curve, i.e. inflation being more responsive to slack when there is a large amount of it than in normal times or booms. For example, this is consistent with firms operating in market structures where they can make different pricing decisions depending on market conditions. When there is a large amount of slack, firms may be more willing to cut prices in order not to lose market share to rival firms. Conversely, firms might be reluctant to increase prices in periods when output is close to or above potential to avoid losing market share.
Convexity and concavity do not need to be mutually exclusive. One way to reconcile the presence of both are "threshold effects", namely a steeper relationship between inflation and slack only for extreme values of the slack variable (e.g. during deep recessions and/or after prolonged periods of above-trend growth). One microeconomic notion consistent with such a set-up is that prices are more responsive when there is a lot of slack (because firms do not want to lose market share) or when firms are operating way above potential (because of higher costs), and less responsive in between (when adjusting factor utilisation is preferred to changing prices). In such a case, the Phillips curve is concave when there is a lot of slack and convex when the economy is operating considerably above potential.
Other microeconomic arguments for non-linearity do not fit the convexity-concavity dichotomy as neatly, but may nonetheless be important. This may either be because they only operate during upturns or downturns, or because they depend on the rate at which slack is closing. Menu costs are one example: when firms face costs to change their prices, typically only a fraction of them will adjust prices in a given period, but it is likely that the larger the demand shock they face, the greater the share of firms adjusting their prices will be. In such a case, the rate at which slack closes (or opens up) will determine the slope of the Phillips curve for any given level of slack.
Chart B
Euro area Phillips curve slopes in two samples across a range of specifications
Note: Slack measures are as in Chart 4, standardised (and inverted where appropriate) for comparability.
Time variation in the coefficients of an otherwise linear Phillips curve is sometimes taken as first-pass evidence of non-linearity in the relationship between slack and inflation. That is because, if the pattern of variation coincides with the economic cycle, then time-varying parameters might be a better fit for outturns that would otherwise look non-linear when viewed in slack/inflation space. Time variation in the coefficients is in itself a form of non-linearity, because the parameters in the equation effectively become variables that depend on time and multiply the independent variables. Broadly speaking, time variation has been tested in two ways: either by simply splitting the sample and comparing fixed parameter estimates, or by estimating models with time-varying parameters. Both approaches provide some evidence of an increase in the slope of the euro area Phillips curve in recent years, although with a high degree of uncertainty. Chart B illustrates the results from the first approach: the same models are estimated over two different samples, and changes in slope across the two samples are illustrated by means of deviations from a 45 degree line.
Quadratic slack terms and other forms of non-linearity have been tested extensively, with mixed results. In an empirical exercise featuring a large number of different specifications, quadratic slack terms (which seek to introduce convexity in the relationship between slack and inflation) were statistically significant in some of the specifications, but, in models that controlled for imported inflation, that significance largely disappeared, consistent with the view that linear models with suitably chosen control variables are even able to fit data well that appear non-linear in a reduced-form relationship (see Chart C). In the same exercise, a dummy variable for positive values of the output gap (in principle able to fit both convex and concave relationships) turned out to be significant only in a fraction of the models.
Chart C
Share of instances in which the non-linear variables in euro area Phillips curve specifications are statistically significant
(percentages)
Sources: Eurostat and ECB staff calculations.
Notes: For two measures of inflation (HICP and HICPX inflation), versions of equation (1) including and excluding external variables and a different form of non-linearity (quadratic terms for economic slack or 0/1 dummy variables for economic slack above/below a certain threshold) are estimated for various measures of slack (see the notes to Chart 4). The bars denote the share of models in which the coefficients on the non-linear terms are statistically significant at the 10% level.
Some evidence in favour of non-linearity comes from considering more sophisticated threshold effects. Models allowing for a steeper slope of the Phillips curve when slack is outside certain bounds help fit the data even when including expectations and imported inflation in the specification. This is the case both when the output gap and when the unemployment gap are used as measures of slack. Using regime-switching Phillips curves, where the slope is allowed to change with the level of the output gap, some evidence of non-linearity was found for the euro area.[26]
Phillips curve models can provide a historical perspective on the relative importance of the main drivers of underlying inflation. Chart 5 summarises the lessons that can be drawn from the thick modelling approach presented in the previous section by showing the average contributions to inflation (all in terms of deviations from their historical averages) of its three main drivers across all models considered.[27] At the onset of the Great Financial Crisis, underlying inflation was well above its historical average, largely explained by the economy running at above normal capacity (see the large contributions from economic tightness). However, as early as the second half of 2009, the inflation gap – the deviation of inflation from its mean – turned negative. To a certain extent, this was due to increasing levels of slack with the unfolding of the ensuing recession, and also to a slight softening of inflation expectations, but part of the weakness cannot be accounted for by our explanatory variables.
Phillips curve-based decomposition of underlying inflation
(annual percentage changes and percentage point contributions; all values in terms of deviations from their averages since 1999)
Source: ECB calculations.
Notes: The bars show average contributions across all the models considered in Section 2. Contributions are derived as in Yellen, J.L., "Inflation Dynamics and Monetary Policy", speech at the Philip Gamble Memorial Lecture, University of Massachusetts, Amherst, 24 September 2015.
The missing disinflation and missing inflation episodes are partly reflected in Phillips curve estimates. The evidence presented in Chart 5 supports the missing disinflation narrative from 2011 onwards, when a large unexplained positive contribution to underlying inflation begins to appear. One explanation put forward for this pointed to a larger impact from external factors during the recovery phase than simple Phillips curve models could capture.[28] In the course of 2013, underlying inflation fell well below its historical average, where it has remained until the present day. The Phillips curve models lend some support to this missing inflation puzzle, as the negative contributions from the residuals indicate the models' inability to fully account for the weakness in inflation over almost the entire period. One explanation is related to "pent-up restraints": while declines in prices and wages during the recession were limited due to downward nominal rigidities, in the early phases of the recovery, price and wage inflation may have been correspondingly subdued.[29] In other words, the missing inflation could have been a consequence of the missing disinflation period, at least in the initial stages of the economic recovery.
Nevertheless, except for the last year or so, estimated Phillips curves can account for much of the weakness in underlying inflation since 2013, imputing the bulk of it to its key determinants rather than to unexplained residuals. The relative importance of the three key inflation drivers has changed throughout this period. Based on the average contributions across models in Chart 5, the drag coming from economic slack dominated the picture in the early part of the period, and continued to play a (diminishing) role until spare capacity in the euro area was largely absorbed. As underlying inflation continued to turn out well below its historical average, some of its weakness began being attributed to lower short-to-medium-term inflation expectations, which exerted a mild drag up to recent quarters. External developments, in the form of lower oil, commodity and other import prices, also began gradually to feed through to underlying inflation. While the negative contributions of these factors had largely faded by early 2018, underlying inflation remained weak throughout 2018.
The more recent weakness in underlying inflation is difficult to explain within the Phillips curve framework. Even within our thick modelling framework, the narrative summarised in Chart 5 is subject to a large degree of uncertainty, as different models impute inflation developments to different factors at any given point in time. In the following subsections, we provide a quantification of the uncertainty around the contributions of slack, inflation expectations and external prices to inflation, and also review some of the economic sources of such uncertainty. The overall picture that emerges is that uncertainty surrounding individual drivers could potentially account for some of the unexplained residuals in Chart 5 until mid-2017, but given the fading contributions of all three main drivers, the more recent weakness in underlying inflation cannot be accounted for by standard Phillips curve models.
Slack played a leading role in explaining underlying inflation from 2013 until 2016. Given the euro area sovereign debt crisis in 2010 and the ensuing recession (2011-2014), it is understandable that explanations of inflation over that period focus on the role of domestic drivers, especially slack, in the euro area.[30] Nevertheless, Phillips curve models do not paint the full picture; the initial fall in underlying inflation after mid-2012 was unexpected, and although slack can account for the bulk of it in Chart 5, unexplained factors also played a major role.[31] Furthermore, the range of contributions of slack to inflation across the 550 models that we estimate is particularly wide over that period (see Chart 6). Two explanations for the difficulty in explaining inflation over that period using simple Phillips curve models are a steepening of the euro area Phillips curve (whereby inflation would follow the business cycle much more closely) and/or a mismeasurement of slack (namely more slack than captured by standard measures).
Range of contributions of slack to underlying inflation
Notes: The shaded area shows the range of contributions of measures of economic slack/tightness to underlying inflation across the 550 models that we estimate (see Section 2); the broken grey line shows the average contribution, which corresponds to the yellow bars in Chart 5. Contributions are derived as in Yellen, J.L., "Inflation Dynamics and Monetary Policy", speech at the Philip Gamble Memorial Lecture, University of Massachusetts, Amherst, 24 September 2015.
Changes in Phillips curve slopes and potential mismeasurement of slack add to the uncertainty surrounding the contribution of slack to inflation. As early as 2014,[32] the ECB discussed the possibility of a stronger relationship between inflation and slack, and lower nominal rigidities in some euro area countries due to structural reforms[33] being implemented are consistent with such a view. Nevertheless, it is challenging to distinguish a change in the Phillips curve slope from a mismeasurement of slack. Alternative estimates of slack, where the output gap is required to be consistent with inflation dynamics within a stable Phillips curve relationship, would have to have been much larger over the missing inflation period.[34] Also, the legacy of the prolonged euro area sovereign debt crisis suggested that the full extent of slack in the labour market could be better captured by broadening the range of labour market indicators, also taking into account workers who became discouraged or worked part-time for economic reasons, but Phillips curves estimated with such measures would still show negative residuals in the more recent period.[35] Moreover, real-time estimates of economic slack can be subject to large measurement error, and revisions are common.[36] Notwithstanding all these sources of uncertainty, Chart 6 suggests that, over the most recent period, the drag from slack has dissipated, making it difficult to look to this factor to account for the unexplained negative residuals in Chart 5 in the last year of the sample.
The decline in survey-based measures of inflation expectations after 2013 raised some concerns that the Phillips curve had shifted downwards, but the message from our estimates is mixed. Over the period from 2014 to mid-2017, Chart 5 shows that inflation expectations might have contributed to the drag on underlying inflation. Nevertheless, as discussed in Section 2, available measures of expectations are imperfect and it is sometimes difficult to interpret the signal they provide for inflation. Chart 7 highlights this uncertainty within our thick modelling framework. The range of the contributions of expectations over the 2014-2017 period can be wide at times, reflecting the fact that it covers measures with various forecast horizons, including both short-to-medium-term survey-based inflation expectations (which can be noisier and more closely trail developments in past inflation) and long-term measures of survey inflation expectations (which, by comparison, have been more stable).
The most recent weakness in underlying inflation does not appear to be explained by developments in inflation expectations. Not only has the average contribution gradually faded towards zero, but the range of contributions across models has also become remarkably small, reflecting the gradual pick-up in the available survey-based measures of inflation expectations.
Range of contributions of inflation expectations to underlying inflation
Notes: The shaded area shows the range of contributions of measures of inflation expectations to underlying inflation across the 550 models that we estimate (see Section 2); the broken grey line shows the average contribution, which corresponds to the red bars in Chart 5. Contributions are derived as in Yellen, J.L., "Inflation Dynamics and Monetary Policy", speech at the Philip Gamble Memorial Lecture, University of Massachusetts, Amherst, 24 September 2015.
Global factors in general, and low oil and other commodity prices in particular, have featured prominently in inflation narratives over recent years.[37] Chart 5 highlights the increasing drag on underlying inflation associated with external price developments from 2015 onwards. Underlying inflation is affected by external price movements through two main channels: a direct one, via the price of imported final consumption goods; and an indirect one, via the price of imported intermediate goods used in production within the euro area. The drop in oil prices starting in mid-2014 was one of the largest since the inception of Economic and Monetary Union (EMU) and left its mark on the headline inflation profile for the subsequent years. For underlying inflation, however, the negative contributions from external price developments were relatively modest when looking at the average contribution across models, but for part of this period could have been substantially larger, according to our range of estimates (see Chart 8). However, over the last few quarters, both the average contribution and the range around it have shrunk substantially.
Range of contributions of external prices to underlying inflation
Notes: The shaded area shows the range of contributions of measures of external prices to underlying inflation across the 550 models that we estimate (see Section 2); the broken grey line shows the average contribution, which corresponds to the green bars in Chart 5. Contributions are derived as in Yellen, J.L., "Inflation Dynamics and Monetary Policy", speech at the Philip Gamble Memorial Lecture, University of Massachusetts, Amherst, 24 September 2015.
Global influences on domestic inflation could extend beyond what can be captured by import and commodity prices alone, but the empirical evidence on additional channels is mixed. In a globalising world, the inflation process might reflect increased trade flows, the integration of emerging economies into the world economy and the rise of global value chains shifting parts of production abroad. All these phenomena can affect inflation via numerous channels, potentially with long lags, and capturing their influence within a traditional Phillips curve model can be empirically challenging. ECB (2017) finds some support for including global measures of slack in a thick modelling Phillips curve framework, but overall the explanatory gains appear to be limited.[38] However, despite the mixed empirical results, the relatively low dispersion of inflation rates across different economies, including in the case of underlying inflation (see Chart 9), suggests that broader structural drivers may be shaping inflation worldwide in ways that are yet to be fully grasped.[39]
Dispersion of underlying inflation rates in OECD countries since 1999
(standard deviations)
Sources: Haver Analytics, ECB and Eurostat.
Note: The line shows the standard deviation across OECD countries excluding Turkey and Slovenia.
Phillips curve models provide a useful and intuitive framework for understanding and communicating inflation developments. We employ a parsimonious, yet not overly simplistic specification that spans the key determinants of inflation beyond the level of economic activity. We combine it with a thick modelling approach that mitigates some of the pervasive model uncertainty, allowing us to draw a more robust inference about the strength of the relationship between inflation and its drivers. Our results provide a plausible narrative for the evolution of underlying inflation in the euro area since the onset of the Great Financial Crisis.
Estimated Phillips curves can account for much of the weakness in underlying inflation between 2013 and mid-2017, while the more recent weakness in underlying inflation remains largely unexplained. The average contributions of slack, inflation expectations and external prices across all estimated models can account for the bulk of the deviations of underlying inflation from its historical average over large spans of the period we consider. However, given the fading contributions of all three factors and the narrowing of uncertainty ranges around them over the most recent period, the persistent weakness in underlying inflation highlights the need for other, complementary, approaches.
Like any other analytical tool, Phillips curves also have limitations and shortcomings. For example, while being intuitive and transparent, reduced-form estimates are, by nature, partial-equilibrium and thus open to both theoretical and empirical objections. Furthermore, to remain tractable, they inevitably miss many aspects (for example, fiscal policy and financial factors) that could nonetheless be important for explaining underlying inflation but require more sophisticated modelling approaches. Finally, statistical and measurement issues can also cause instability in Phillips curve relationships over specific periods of time. Despite these shortcomings, Phillips curve models are an integral part of a much broader analytical toolkit deployed by central banks to understand the inflation process. They have often provided relevant insights, at times leading the way for more sophisticated approaches and at other times offering a cross-check for analyses or forecasts originating elsewhere. The very lively debate surrounding them bears testimony to their usefulness.
[1]Coibion, O. and Gorodnichenko, Y., "Is the Phillips Curve Alive and Well after All? Inflation Expectations and the Missing Disinflation", American Economic Journal: Macroeconomics, Vol. 7(1), 2015, pp. 197-232; Ciccarelli, M. and Osbat, C. (eds.), "Low inflation in the euro area: Causes and consequences", Occasional Paper Series, No 181, ECB, 2017.
[2]Constâncio, V., "Understanding Inflation Dynamics and Monetary Policy", panel remarks at the Jackson Hole Economic Policy Symposium, Federal Reserve Bank of Kansas City, 29 August 2015; Bobeica, E. and Jarociński, M., "Missing Disinflation and Missing Inflation: A VAR Perspective", International Journal of Central Banking, Vol. 15(1), 2019, pp. 199-232.
[3]See Box 3 in the article entitled "The euro area labour market through the lens of the Beveridge curve" in this issue of the Economic Bulletin.
[4]See Yellen, J.L., "Inflation Dynamics and Monetary Policy", speech at the Philip Gamble Memorial Lecture, University of Massachusetts, Amherst, 24 September 2015. Yellen, J.L., "Inflation, Uncertainty and Monetary Policy", speech at the 59th Annual Meeting of the National Association for Business Economics, Cleveland, Ohio, 26 September 2017.
[5]Powell, J., "Monetary Policy and Risk Management at a Time of Low Inflation and Low Unemployment", speech at the 60th Annual Meeting of the National Association for Business Economics, 2 October 2018.
[6]Williams, J.C., "Discussion of 'Prospects for Inflation in a High Pressure Economy: Is the Phillips Curve Dead or Is It Just Hibernating?' by Peter Hooper, Frederic S. Mishkin, and Amir Sufi", remarks at the 2019 US Monetary Policy Forum, Federal Reserve Bank of New York, 22 February 2019.
[7]Williams (2019), op. cit.; and Hooper, P., Mishkin, F.S. and Sufi, A., "Prospects for Inflation in a High Pressure Economy: Is the Phillips Curve Dead or is It Just Hibernating?", paper presented at the 2019 US Monetary Policy Forum, February 2019. For a theoretical derivation of a non-linear Phillips curve, see Benigno, P. and Ricci, L., "The Inflation-Output Trade-Off with Downward Wage Rigidities", American Economic Review, Vol. 101(4), 2011, pp. 1436-1466; for an empirical review of the evidence, see, e.g., Albuquerque, B. and Baumann, U., "Will US inflation awake from the dead? The role of slack and non-linearities in the Phillips curve", Journal of Policy Modeling, Vol. 39(2), 2017, pp. 247-271.
[8]This result, and the accompanying caveat, parallels some of the findings on the potential non-linearity of the Phillips curve relationship in the euro area discussed in Box 2.
[9]See, for example, Iwasaki, Y., Muto, I. and Shintani, M., "Missing Wage Inflation? Downward Wage Rigidity and the Natural Rate of Unemployment", Bank of Japan Research Laboratory Series, No 18-E-3, 2018; Hara, N., Kazuhiro, H. and Ichise, Y., "Changing Exchange Rate Pass-Through in Japan: Does It Indicate Changing Pricing Behavior?", Bank of Japan Working Paper Series, No 15-E-4, 2015.
[10]Harada, Y., "Economic Activity, Prices and Monetary Policy in Japan," speech, Ishikawa, Japan, 4 July 2018.
[11]"The Phillips curve relationship in the euro area", Monthly Bulletin, ECB, July 2014.
[12]Granger, C.W.J. and Jeon, Y., "Thick modeling", Economic Modelling, Vol. 21(2), 2004, pp. 323-343.
[13]For a discussion of this specification, see Ciccarelli and Osbat, eds. (2017), op. cit. Phillips curve relationships are also part of richer structural models; in this article we focus on reduced-form evidence, mainly for the sake of simplicity of exposition.
[14]All three types of measure are explained and discussed in Ehrmann, M., Ferrucci, G., Lenza, M. and O'Brien, D., "Measures of underlying inflation for the euro area", Economic Bulletin, Issue 4, ECB, 2018.
[15]See the notes to Chart 4 for the list of measures of slack considered.
[16]One exception, where instead the labour share of income is used as a measure of real marginal costs, is Galí, J. and Gertler, M., "Inflation dynamics: A structural econometric analysis", Journal of Monetary Economics, Vol. 44(2), 1999, pp. 195-222.
[17]Blanchard, O., Cerutti, E. and Summers, L.H., "Inflation and Activity: Two Explorations and Their Monetary Policy Implications", Working Paper Series, No WP 15-19, Peterson Institute for International Economics, 2015; Jarociński, M. and Lenza, M., "An Inflation-Predicting Measure of the Output Gap in the Euro Area", Journal of Money, Credit and Banking, Vol. 50(6), 2018, pp. 1189-1224; Chan, J.C.C., Koop, G. and Potter, S.M., "A Bounded Model of Time Variation in Trend Inflation, Nairu and the Phillips Curve", Journal of Applied Econometrics, Vol. 31(3), 2016, pp. 551-565.
[18]See Ball, L. and Mazumder, S., "A Phillips Curve with Anchored Expectations and Short-Term Unemployment", Journal of Money, Credit and Banking, Vol. 51(1), 2019, pp. 111-137, and the references therein.
[19]See Szörfi, B. and Tóth, M., "Measures of slack in the euro area", Economic Bulletin, Issue 3, ECB, 2018.
[20]We consider the following inflation expectation measures: (1-7) Consensus Economics measures with a horizon of two to seven quarters ahead and interpolated long-term Consensus Economics expectations; (8-11) ECB Survey of Professional Forecasters measures, one year ahead, two years ahead and five years ahead.
[21]Coibion and Gorodnichenko (2015), op. cit., point to the difference between the inflation expectations of professional forecasters and of firms, arguing that the latter are better approximated by the expectations of consumers.
[22]As external variables, we employ: (1) annual change in the prices of imports from outside the euro area; (2) annual change in oil prices in euro; (3) a longer-term average of past oil price changes; (4-5) annual global headline and underlying inflation, all with appropriately long lags.
[23]Matheson, T. and Stavrev, E., "The Great Recession and the inflation puzzle", Economics Letters, Vol. 120(3), 2013, pp. 468-472; Forbes, K.J., "How Have Shanghai, Saudi Arabia, and Supply Chains Affected U.S. Inflation Dynamics?", Federal Reserve Bank of St. Louis Review, Vol. 101(1), First Quarter 2019, pp. 27-43.
[24]"Domestic and global drivers of inflation in the euro area", Economic Bulletin, Issue 4, ECB, 2017.
[25]See, for example, Leduc, S., Marti, C. and Wilson, D.J., "Does Ultra-Low Unemployment Spur Rapid Wage Growth?", FRBSF Economic Letter, No 2019-02, Federal Reserve Bank of San Francisco, 2019.
[26]Gross, M. and Semmler, W., "Mind the output gap: the disconnect of growth and inflation during recessions and convex Phillips curves in the euro area", Working Paper Series, No 2004, ECB, 2017.
[27]This is an ex post analysis involving the full sample, but a real-time one would have painted a similar picture for the low-inflation period.
[28]Constâncio (2015), op. cit.; Ciccarelli and Osbat, eds. (2017), op. cit.; and Bobeica and Jarociński (2019), op. cit. Increases in VAT in some euro area countries over the period could also account for part of this unexplained contribution, but only to a limited extent.
[29]Praet, P., "Price stability: a sinking will-o'-the-wisp?", IMF Spring Meetings Seminar, Washington, D.C., 16 April 2015.
[30]Ciccarelli and Osbat, eds. (2017), op. cit.
[31]This is a point about changes in, rather than the level of, inflation: the main contributor to the peak-to-trough fall in inflation is the change in the contribution from the residual rather than that from slack.
[32]ECB (2014), op. cit.
[33]Izquierdo, M., Jimeno, J.F., Kosma, T., Lamo, A., Millard, S., Rõõm, T. and Viviano, E., "Labour market adjustment in Europe during the crisis: microeconomic evidence from the Wage Dynamics Network survey", Occasional Paper Series, No 192, ECB, June 2017.
[34]Jarociński and Lenza (2018), op. cit.
[35]Cœuré, B., "Scars or scratches? Hysteresis in the euro area", speech at the International Center for Monetary and Banking Studies, Geneva, 19 May 2017. This argument is one of the reasons for including broad unemployment measures in our estimates (see the notes to Chart 4).
[36]See Szörfi and Tóth (2018), op. cit.
[37]For example, "External environment", Economic Bulletin, Issue 8, ECB, 2015, noted that "global inflation has remained very low, reflecting the fall in oil prices".
[38]See "Domestic and global drivers of inflation in the euro area", Economic Bulletin, Issue 4, ECB, 2017; and Nickel, C., "The role of foreign slack in domestic inflation in the Eurozone", VOX, CEPR Policy Portal, 28 July 2017.
[39]See also Forbes (2019), op. cit.
Economic Bulletin – online statistics


To Alexander Bikenore, T. of Ire., or his deputy and the barons of the Dublin Ex..
Thomas Bonde was, by order of the Jcr, with the K.'s forces at Castledermot on 26 July last, and so could not be in the Ex. on that day to answer William the chaplain in a plea of debt. ORDER not to place Thomas in default by reason of his absence.
NAI, RC 8/6, p. 25.


CRG Roll a Click levers are amazing...does anyone know how the vortex levers are? better or worse then CRG?
Superstreetbike did a lever comparison a couple of months ago. They wrote reviews and scored them according to fit, style, functionability, and some other basic criteria. CRG's and Pazzo's rated the best with the same score. The others fell a little short in some areas which prompted me to purchase the CRG. I really like them, well worth the money. The Pazzo's rated the same and they are $140 shipped on EBAY.
It's rare to find them on ebay for $140. Pazzo hasvery strict dealer guidelines. If you get caught selling them for under $159 they revoke your dealer account. I know this because I've just picked up a dealer account for Pazzo and will be adding them to our site soon.
The CRG's are awesome. Everyone else pretty much copied them in some shape or form. Pazzo, Vortex, Titan etccc. They are all great levers though. Yea, $140 for Pazzo's I would beware. The lowest MAP for dealers is $159 set by Pazzo. So most people advertising them for under $159 are probably not authorized dealers.


text:
"Love and Monsters" brings sweetness to the post-apocalypse
by Tim Stevens October 17, 2020 October 17, 2020
Dylan O'Brien turns the end of the world into a call for empathy in this sweet take on the genre.
As Joel Dawson (Dylan O'Brien) tells us in the most casual way possible, the world has ended. Via a montage of Dawson's drawings, we learn of an asteroid Agatha-616 (a sly reference for longtime comic fans?) that seemed set to send the human race in the same historical dustbin as the dinosaur. The nations of the world, however, came together and blow the damn thing up. Crisis averted. The resulting debris and fallout, though, mutated the cold-blooded creatures on Earth into oversized bloodthirsty versions of themselves. Humankind fights, humankind ends up dying to the tune of 90% population reduction. What's left of our ranks now live in small communities underground, huddling, hoarding, and hoping for some kind of change while running out the clock.
From the opening narration, the film immediately marks itself as a sort of sweeter, more optimistic cousin to Zombieland. O'Brien relates the ridiculous heightening of our personal apocalypse—the threat of a planet-killing asteroid giving way to literal monsters—with delightful charm. It serves to both establish Dawson's personality but also to establish the state of things. In the seven years since the end, people have rediscovered the art of humorous detachment.
Overall, O'Brien establishes himself as a likable lead and guide to the world. His lack of hardening allows him to start as a comedic figure. However, both O'Brien and the script by Brian Duffield and Matthew Robinson keeps things flexible enough that when Dawson's tragic backstory unfurls it adds depth rather than breaking the character.
When Dawson takes on traveling companions, be it a dog named Boy or the mismatched duo of Clyde Dutton (Michael Rooker, lowkey gruff and charming) and Minnow (a just precocious enough Ariana Greenblatt), O'Brien makes him so fundamentally decent, you understand how he seems to bring out empathy in everyone he meets.
The real draw here though is the creature designs. Recognizable as the amphibians, reptiles, fish, and bugs outside your door right now but more than just bigger, they manage to play both funny to the viewer and entirely "legible" as frightening to the protagonists. Additionally, save for a beach scene, they nicely integrate into the physical space with a sense of presence and weight. Even when things do feel false, there is a kind of higher-tech Harryhausen charm to the beasties.
Structurally, the movie falters a bit the closer Dawson gets to his former girlfriend Aimee's (Jessica Henwick) camp. The monster encounters begin to feel less like discovery and more like checking things off a list. Here is the one where he proves to himself he can do it, here's the one with the scariest monster, here's the one where he learns a bigger lesson, and so on. The individual scenes work fine on their own, but, as an integrated whole, it loses some charm as the seams become all too obvious.
Accidentally or not, the film's appreciation of living after circumstances have overthrown the life you took for granted meets the moment.
Still, director Michael Matthews does find time to inject moments of beauty and humanity even as the movie starts to feel like it's on rails. A light show provided by a school of formerly aquatic creatures and a bittersweet reunion of sorts come quickly to mind. Again, the film's willingness to find heart in the wasteland asserts itself as its more endearing and enduring quality.
At the end of the day, Love and Monsters is not an especially new take on its themes. However, I expect I will be coming back to Dawson's thoughts of how it feels to taste freedom after so long underground more than once in the months to come. Accidentally or not, the film's appreciation of living after circumstances have overthrown the life you took for granted meets the moment. As we all stand on the precipice of what could very well turn into a second pandemic lockdown, its bittersweet hug of a story settles in nicely around the viewer.
Love and Monsters is currently available on demand.
Love and Monsters Trailer:
2020apocalypsedylan o'brienmichael matthewsmichael rooker
Tim Stevens
Tim Stevens is a freelance writer and therapist from the Nutmeg State, hailing from the home of the World's Smallest Natural Waterfall. In addition to The Spool, you can read his stuff in CC Magazine, Marvel.com, ComicsVerse, and The New Paris Press. His work has been quoted in Psychology Today, The Atlantic, and MSN Ireland. And yes, he is listing all this to try and impress you.
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Criterion Corner
Criterion Corner: Luis Buñuel, "Minding the Gap", "Rolling Thunder Revue"
January's Criterion offerings include a box set of Bunuel's final films, Martin Scorsese on Bob Dylan, and Bing Liu's astonishing doc debut.
Next: AFI Fest: "76 Days" takes us inside Wuhan's COVID lockdown
Reading: "Love and Monsters" brings sweetness to the post-apocalypse

redpajama_set_name: RedPajamaCommonCrawl


text:
Patti Warashina
As an artist, the human figure has fascinated me for most of my career since the early 60's. I believe my sustaining interest in the human figure is probably due to the fact that my own body is the closest resource from which I draw my ideas. The human body is also an image that gives affirmation of my own existence, and serves as a visual diary and marker of time. It also documents and reflects the civilization in which I live.
Perhaps this sustaining interest is also a continuation from my female childhood fascination with play-acting with dolls. I have legitimized this imaginary behavior in my adult years by working as an artist, modeling human sculptures in illusory states in which I control a personal story line. At times I draw parallels to nature and human communities by using complex arrangements that I find fascinating in my observation of nature and its teeming energy. At other times I draw imagery from the interwoven parts of human behavior found in every day life, or in observing societal concerns. Using sources such as these, I am able to satisfy the visual curiosity that appears in my own mind's eye.
In my earlier work, I portrayed the human body "realistically" to persuade the viewer to step into the authenticity of the scenario of the work. Over time, however, my exploration of the figure has continued to move away and evolve from a realistic representation of the human body into a simpler, reductive but exaggerated form, with details left for extremities and facial features in order to tie the body back into some sense of reality.
My current work involves further analyses of the figure by exploring the surface in a purely two-dimensional inquiry. This allows me to minimize embellishment and color through simple abstract form as a reference to an unspecified time. I want the two-dimensional surface work to seem independent of the three-dimensional form of the figure, as though it is passing over the figure, thereby giving illusion to two independent spatial realities coinciding with one another. This reductive abstract surface has seemed to further eliminate the reality of realistic surface painting, in this case clothes, and works in tandem with the simplification of the body and form.
What has remained with the figure over time is the narrative nature of the subject matter and details of facial features and extremities. The elimination of these components in future exploration remains to be seen.


1st! @ 2011 AOBA National Show!
This is obvious in the 10x champion true black son, AutumnSun's Black Maelstrom. We were fortunate to have had our program benefit from such an exceptional offspring, especially as he was just one of only a few we have performed to Secret! We have the fortune of several excellent herdsires, including grey and black, so Secret has had to be patient. And, Maelstrom is just as a precocious stud just as his sire, as both started breeding under 2 years old, so Secret's competition is increasing. Secret is standing in the shadow of his champion son Maelstrom, so we would consider selling him for the right offer. His is a special bloodline, greatly limited by chance to be nearly exclusive to our farm.
Color Champion - 2011 GWAS. Over 43 bay and true black males.
4th - 2010 GWAS, Juvenile Black Male, Jill MacLeod - GWAS, a level 5 show and the largest show in the country that year (15 TB & 12 BB juveniles in 2 classes, 19 TB yearling (2 classes)... well, you get the picture). These were tough classes!


text:
#include "modules/skottie/utils/SkottieUtils.h"

namespace skottie_utils {

class CustomPropertyManager::PropertyInterceptor final : public skottie::PropertyObserver {
public:
    explicit PropertyInterceptor(CustomPropertyManager* mgr) : fMgr(mgr) {}

    void onColorProperty(const char node_name[],
                         const LazyHandle<skottie::ColorPropertyHandle>& c) override {
        const auto key = fMgr->acceptKey(node_name);
        if (!key.empty()) {
            fMgr->fColorMap[key].push_back(c());
        }
    }

    void onOpacityProperty(const char node_name[],
                           const LazyHandle<skottie::OpacityPropertyHandle>& o) override {
        const auto key = fMgr->acceptKey(node_name);
        if (!key.empty()) {
            fMgr->fOpacityMap[key].push_back(o());
        }
    }

    void onTransformProperty(const char node_name[],
                             const LazyHandle<skottie::TransformPropertyHandle>& t) override {
        const auto key = fMgr->acceptKey(node_name);
        if (!key.empty()) {
            fMgr->fTransformMap[key].push_back(t());
        }
    }

    void onTextProperty(const char node_name[],
                        const LazyHandle<skottie::TextPropertyHandle>& t) override {
        const auto key = fMgr->acceptKey(node_name);
        if (!key.empty()) {
            fMgr->fTextMap[key].push_back(t());
        }
    }

private:
    CustomPropertyManager* fMgr;
};

class CustomPropertyManager::MarkerInterceptor final : public skottie::MarkerObserver {
public:
    explicit MarkerInterceptor(CustomPropertyManager* mgr) : fMgr(mgr) {}

    void onMarker(const char name[], float t0, float t1) override {
        const auto key = fMgr->acceptKey(name);
        if (!key.empty()) {
            fMgr->fMarkers.push_back({ std::move(key), t0, t1 });
        }
    }

private:
    CustomPropertyManager* fMgr;
};

CustomPropertyManager::CustomPropertyManager()
    : fPropertyInterceptor(sk_make_sp<PropertyInterceptor>(this))
    , fMarkerInterceptor(sk_make_sp<MarkerInterceptor>(this)) {}

CustomPropertyManager::~CustomPropertyManager() = default;

sk_sp<skottie::PropertyObserver> CustomPropertyManager::getPropertyObserver() const {
    return fPropertyInterceptor;
}

sk_sp<skottie::MarkerObserver> CustomPropertyManager::getMarkerObserver() const {
    return fMarkerInterceptor;
}

template <typename T>
std::vector<CustomPropertyManager::PropKey>
CustomPropertyManager::getProps(const PropMap<T>& container) const {
    std::vector<PropKey> props;

    for (const auto& prop_list : container) {
        SkASSERT(!prop_list.second.empty());
        props.push_back(prop_list.first);
    }

    return props;
}

template <typename V, typename T>
V CustomPropertyManager::get(const PropKey& key, const PropMap<T>& container) const {
    auto prop_group = container.find(key);

    return prop_group == container.end()
            ? V()
            : prop_group->second.front()->get();
}

template <typename V, typename T>
bool CustomPropertyManager::set(const PropKey& key, const V& val, const PropMap<T>& container) {
    auto prop_group = container.find(key);

    if (prop_group == container.end()) {
        return false;
    }

    for (auto& handle : prop_group->second) {
        handle->set(val);
    }

    return true;
}

std::vector<CustomPropertyManager::PropKey>
CustomPropertyManager::getColorProps() const {
    return this->getProps(fColorMap);
}

skottie::ColorPropertyValue CustomPropertyManager::getColor(const PropKey& key) const {
    return this->get<skottie::ColorPropertyValue>(key, fColorMap);
}

bool CustomPropertyManager::setColor(const PropKey& key, const skottie::ColorPropertyValue& c) {
    return this->set(key, c, fColorMap);
}

std::vector<CustomPropertyManager::PropKey>
CustomPropertyManager::getOpacityProps() const {
    return this->getProps(fOpacityMap);
}

skottie::OpacityPropertyValue CustomPropertyManager::getOpacity(const PropKey& key) const {
    return this->get<skottie::OpacityPropertyValue>(key, fOpacityMap);
}

bool CustomPropertyManager::setOpacity(const PropKey& key, const skottie::OpacityPropertyValue& o) {
    return this->set(key, o, fOpacityMap);
}

std::vector<CustomPropertyManager::PropKey>
CustomPropertyManager::getTransformProps() const {
    return this->getProps(fTransformMap);
}

skottie::TransformPropertyValue CustomPropertyManager::getTransform(const PropKey& key) const {
    return this->get<skottie::TransformPropertyValue>(key, fTransformMap);
}

bool CustomPropertyManager::setTransform(const PropKey& key,
                                         const skottie::TransformPropertyValue& t) {
    return this->set(key, t, fTransformMap);
}

std::vector<CustomPropertyManager::PropKey>
CustomPropertyManager::getTextProps() const {
    return this->getProps(fTextMap);
}

skottie::TextPropertyValue CustomPropertyManager::getText(const PropKey& key) const {
    return this->get<skottie::TextPropertyValue>(key, fTextMap);
}

bool CustomPropertyManager::setText(const PropKey& key, const skottie::TextPropertyValue& o) {
    return this->set(key, o, fTextMap);
}

} // namespace skottie_utils

redpajama_set_name: RedPajamaGithub


The rich and proud rugby heritage of Poverty Bay and nearby East Coast will be celebrated when the New Zealand Rugby Union and the Poverty Bay Rugby Union jointly host the fifth of this year's All Blacks Capping Ceremonies in Gisborne on Friday September 4.
The ceremony will be held at Gisborne's Emerald Hotel and will officially confer All Blacks Test caps on 10 players who originated from or had ties to that part of New Zealand.
Among them will be All Blacks captain Ian Kirkpatrick, 23-Test veteran Richard "Tiny" White and two All Blacks – Brian Fitzpatrick and Hamish Macdonald, who both had sons who went on to become All Blacks.
NZRU Chairman Jock Hobbs said the NZRU was delighted to be partnering with the Poverty Bay Rugby Union and community to honour their local heroes.
Poverty Bay Chairman Malcolm Maclean said the union is very honoured to have been given the opportunity by the NZRU to host an All Blacks Capping Ceremony.
The former All Blacks will also be introduced to the crowd at the Poverty Bay v North Otago, Heartland Championship match on Saturday.
^ Province refers to the province the player was playing for at the time of their Test debut.
* Family members of those players who have passed away will collect the caps on their behalf.
While four of the players were selected to the All Blacks while playing for Poverty Bay and another from East Coast, each of the players being honoured on Friday have had strong links to the region.
The Gisborne event is the fifth of six ceremonies being held around the country in 2009. The final capping ceremony of the year will be held on Friday September 11 in Hamilton on the eve of the All Blacks-Springboks Investec Tri Nations clash.


text:
Q: Timer keeps looping I got this timer (timer2) and it runs every 60 seconds..
And I got this second timer (timer4)
when 60 seconds are over, the timer2_Tick does a few things and initiates timer4.
timer 4 makes sure to wait 4 seconds before coming  in action (I need 4 seconds to be sure that all the downloaded data is there)
when these 4 seconds are over the timer should change an image and it does..
So it all works..
The problem is that every 4 seconds the image blinks.. the image is inside an datta template..
how do I stop that..?? do i need the Stop() or do I need an running counter..??
please help this is driving me nuts..
    private void timer2_Tick(object sender, EventArgs e )
    {
        locationTextBox2.Text = "";

        if (locationTextBox2.Text == "")
        {
            Weatherframe.Source = (ImageSource)new ImageSourceConverter().ConvertFromString("");
        }

        Weatherframe2.Source = Weatherframe.Source;

        System.Windows.Threading.DispatcherTimer timer4 = new System.Windows.Threading.DispatcherTimer();
        timer4.Interval = new TimeSpan(0, 0, 0, 4, 000); // 500 Milliseconds
        timer4.Tick += new EventHandler(timer4_Tick);
        timer4.Start();

    }

    void timer4_Tick(object sender, EventArgs e)
    {
        if (locationTextBox2.Text == String.Empty)
        {
            locationTextBox2.Text = textBlock2.Text;
        }
    }

A: You never stop the timer, so it will keep ticking every fourth second.
Just call Stop on the timer in the handler, but for that you need to keep the reference to the timer in a member variable so that you can access it after you created it.
System.Windows.Threading.DispatcherTimer timer4;

private void timer2_Tick(object sender, EventArgs e )
{
    locationTextBox2.Text = "";

    if (locationTextBox2.Text == "")
    {
        Weatherframe.Source = (ImageSource)new ImageSourceConverter().ConvertFromString("");
    }

    Weatherframe2.Source = Weatherframe.Source;

    timer 4 = new System.Windows.Threading.DispatcherTimer();
    timer4.Interval = new TimeSpan(0, 0, 0, 4, 000); // 500 Milliseconds
    timer4.Tick += new EventHandler(timer4_Tick);
    timer4.Start();

}

void timer4_Tick(object sender, EventArgs e)
{
    timer4.Stop();
    if (locationTextBox2.Text == String.Empty)
    {
        locationTextBox2.Text = textBlock2.Text;
    }
}

A: You should probably listen to when the image has actually been downloaded rather than guess that it takes 4 seconds. You can do that by subscribing to the DownloadCompleted event on BitmapSource
http://msdn.microsoft.com/en-us/library/system.windows.media.imaging.bitmapsource.downloadcompleted.aspx
You should probably also listen for DownloadFailed and DecodeFailed to detect errors.

A: void timer4_Tick(object sender, EventArgs e)
{
    if (locationTextBox2.Text == String.Empty)
    {
        locationTextBox2.Text = textBlock2.Text;
        System.Windows.Threading.DispatcherTimer theTimer = sender as System.Windows.Threading.DispatcherTimer;
        theTimer.Stop();
    }
}

redpajama_set_name: RedPajamaStackExchange


text:
Turn Off the Radio: The Mixtape Vol. 1 est une mixtape de dead prez, sortie le .

L'album s'est classé  au Top Independent Albums et  au Top R&B/Hip-Hop Albums.

Liste des titres

Notes et références

Album de dead prez
Album musical sorti en 2002
Mixtape

redpajama_set_name: RedPajamaWikipedia


text:
Manfred Baur (* 1959 in Marktoberdorf) ist ein deutscher Autor und Dokumentarfilmer.

Baur studierte Chemie, Logik und Wissenschaftstheorie und wurde in Chemie promoviert. Danach war er als Wissenschaftlicher Mitarbeiter in der Halbleiterentwicklung tätig. Seit 1993 ist er Dokumentarfilmer und Wissenschaftsjournalist. So verfasste er mehrere Bände der Was-ist-was-Reihe.

Baur ist Vater zweier Kinder.

Filmographie (Auswahl)
 1999: Feuer im Eis
 2001: Die Odyssee des Menschen
 2006: Metropolis II – Cities of the Dark Ages
 2003–2007: Metropolis – Die Macht der Städte
 2009: Die Eroberung der Alpen

Weblinks

Einzelnachweise

Dokumentarfilmer
Sachbuchautor
Deutscher
Geboren 1959
Mann


Mitra, as a god of justice is the Archangel Michael's prototype. Mitra does not appear in the Gathas, but later appears in the Avesta. In the last days of the Persian Empire, in addition to Ahura Mazda, Mitra and Anahita, goddess of the waters, were also worshipped. The Romans commemorated Mitra as Sol Invictus, the Unconquered Sun. All the Platonists were students of both Zoroastrian soothsayers and mystical Mitraism. In Greek inscriptions, Mitran priests were named Magus. The three Magi who came to visit the birthplace of Jesus were Mitran priests.
Zoroaster stated that the Lord God is Light; which had already been said by Moses. The Prophet Mani (3rd century CE) taught that light was spiritual, hence good and that darkness was material, hence evil. Again Mani preached that there is a spark of light within every human and in that lies the hope of salvation. Mazdak (6th century CE) stressed the pure nature of fire, soil and water. Also, Islam teaches that Allah is light both on this earth and in the heavens.
In the 6th century BCE, Zoroastrianism became the officially recognised state religion of the Persian Empire and was therefore practised over a vast area, from Greece to Egypt and northern India. During the Sasanian era, (3rd to 7th centuries CE), Zoroastrianism continued as the established religion of the country. However, while the Persian Empire showed tolerance toward various faiths, the Sasanians were intolerant of other beliefs. In this period, Zoroastrian priests held the most significant power after the monarchy, and this shook Zoroastrian faith. Zoroaster preached the doctrine of two spirits but his philosophy was not truly dualistic. Dualistic thinking was introduced into the religion at later stages, during the Sasanian era. And later, Zurvanism, which is a modified form of Zoroastrianism, brought out Ohrmazd and Ahriman as the dual jointly eternal principles of good and evil. Ohrmazd is good through his own nature, while Ahriman is evil; the former is the Creator, the latter is the Destroyer. Zurvanism is intrinsically contrary to genuine Zoroastrianism because it is pessimistic and fatalistic. This dualistic doctrine gradually took the place of the monotheism expressed in the Gathas.
Following the Arab invasion and occupation, those loyal to Zoroaster fled, carrying with them Iran's sacred flame, and took refuge first in the hills of Khorasan, and when found there, on the Isle of Hormoz. On suffering persecution there, they escaped by ship to India. It is said that one group travelled overland through the Punjab. The Hindu Prince in south Gujarat allowed them to settle there and awarded them a site on which to build their fire-temple. In return, the Zoroastrians promised to live in peace with the native population, to assist them in time of war, to adopt native dress and language and to make appropriate changes in their marriage customs. The immigration to India took place between the 8th and 9th centuries. The descendants of Persian Zoroastrians in India are known as Parsees. Their name means Persians. Today, most of them live in Mumbai, Bangalore (Karnataka) and Karachi (Pakistan).
India – Kolkata, Parsee Temple.
Avesta or Zend Avesta (the Zoroastrian scriptures) is the sacred books which codify or systematise the teachings of Zoroaster and set out the practices of religious services. It is said that the original books were lost when Alexander the Great burned down the royal palace of Persepolis in 331 BCE. The Avesta of today was put together from the surviving fragments of the original texts during first the Parthian and later the Sasanian eras. It comprises five sections: the Gathas are the songs or hymns composed from what were thought to be the sayings of Zoroaster; the Yasna sets out the major act of worship; in the Vispered are found the oaths of allegiance to spiritual leaders; the Vendidat codifies the rules of Zoroastrian faith regarding both acts of worship and behaviour in life apart from formal worship; the Yashts (the Parsees liturgical book) comprise 21 hymns and recount the legends concerning angels and ancient heroes.
The Gathas are very different from the other sections of Avesta, whose texts are composed from the oldest surviving fragments of the original, and date from the time of Zoroaster. The author of the Gathas, which contain Zoroaster's life philosophy, is not known for certain. The hymns are thought to have come down to the present virtually unchanged over the centuries. The language used in the original Avesta was Avestan, an ancient Iranian language. Later in the 9thcentury CE texts written in Pahlavi, a dialect of Persian. It is claimed that, in the Pahlavi commentaries, religious ideals were devalued and the ancient Gathas, Yasna and Yashts contained more uplifting thoughts.
Dead bodies are considered to be where Angra Mainyu holds sway, so they cannot be buried in the ground, nor at sea. They cannot be cremated either, in order not to pollute the earth, sea and fire. In all the rituals performed for the dead, the "Tower of Silence" plays a vital part. The Tower of Silence, tall, cylindrical and open to the sky above, are enclosed in a thick wall. The only entrance is through a door on the east side of the wall, which is kept locked. Inside, it comprises three concentric circles, for men, women and children. The naked corpse is placed within, where it is exposed to vultures who pick the bones clean. Once dried by the sun, the bones are then swept into a central well. Just in the centre is a deep, round crater, at the bottom of which are spread sand and coal dust, layer upon layer, acting as a filter for all the fluids which drain into it. Thus, all liquids soaking into the soil are filtered and rendered harmless.
The dead, who cannot be touched by anyone save the body-bearers, are carried into the tower on stretchers during the hours of daylight. The porters of the dead are a special class of people who are cared for and paid regularly by the community for this specific purpose, and who do not undertake any other duty but this. The funeral procession is followed by close relatives as far as the Tower of Silence, but no one except the corpse-bearers can enter.
Feeding carrion birds with the flesh of dead bodies displays the Zoroastrian concept of virtue. The soul is presumed to have left the body by the fourth morning after death, and to have reached the next world and presented itself for judgement. The Towers are located near to the city but are built on high ground far from human habitation.
No memorial is erected for the dead. The most important part of the Zoroastrian death ceremony is the prayers said for the departed whose anniversary of death is always commemorated. Each family pays tribute to its dead with fire, frankincense, offerings and the recital of Gathas. The first month of the year is named after the dead. They hold six seasonal feasts, one of which is for the dead.
Decrease in the Zoroastrian population and depletion in the number of vultures as a result of urbanisation have led to a greatly reduced number of Towers of Silence operating. A few Towers of Silence are still in existence in Tehran, Yazd and Mumbai. However, toward the middle of the 20th century, their traditional use in Iran was brought to an end.
Zoroastrians will be obliged to find solutions, such as the use of chemicals, which do not violate their basic religious principles.
Iran – Yazd, a Tower of Silence.


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Q: How to translate a javascript code snippet using `Array.from` to Parenscript (Common Lisp library)? I have this code snippet working on the browser using JavaScript:
Array.from(document.querySelectorAll('input'))

Thedocument.querySelectorAll('input') gets a NodeList and Array.from converts it to an array.
I am trying to translate it to Parenscript inside a function as:
(ps:chain  array (from  (ps:chain document (query-selector "input")))))

This is close:
"array.from(document.querySelector('input'));"

There is even a little trick to achieve the capital letter with the hyphenating of -array:
(ps:ps   (ps:chain  -array (from  (ps:chain document (query-selector "input")))))

Which generates:
"Array.from(document.querySelector('input'));"

But it does not work as expected when called. It returns an empty string.
How can I fix it?
Obs.: I am using Common Lisp/SBCL.

A: Currently, Parenscript only returns primitive values which are:

*

*Undefined;

*Boolean;

*Number;

*String;

*BigInit; and,

*Symbol.

The code document.getElementsByTagName('input') is not returning a
string, it is returning some objects. That's why it fails to work.
Source.


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Q: Showing the position in jCarouselLite I'm using jcarousellite for a simple JQuery carousel, but I would like to alter it a bit so that images are hidden for the items to the far left and the far right, but shown on the middle items.
To do this though I need to be able to find which list items are being displayed in the view port at any one time. I've tried digging around in the source code and using the included callbacks, but I can't ever get index numbers which tally with the item being shown.
Does anyone have any experience of this or ideas on how to solve it?
EDIT
OK solved this to some extent, but it's still not working correctly. The afterEnd function is built into the plugin and provides an object of the currently visible items. I've used this to provide the IDs of the list elements, and apply some transitions.
The problem is that this is all "outside" of the plugin, so if I enable auto scrolling, all this code is ignored. I need some way of inserting this code into the functions within the plugin, and that's where I'm a bit stuck I'm afraid.
    $(".ccvi-carousel").jCarouselLite({
    btnNext: ".next",
    btnPrev: ".prev",
    speed:  800,
    //auto: 2000,
    afterEnd: function(a) {
        if (start=true) {
            $('li#1 .cf-img').hide();
        }
        left = $(a[0]).attr("id");
        mid = $(a[1]).attr("id");
        right = $(a[2]).attr("id");
        $('.prev').click(function() {
            $('li#' + left + ' .cf-img').fadeIn();
            $('li#' + mid + ' .cf-img').hide();
            $('li#' + right + ' .cf-img').hide();
        });
        $('.next').click(function() {
            $('li#' + left + ' .cf-img').hide();
            $('li#' + mid + ' .cf-img').hide();
            $('li#' + right + ' .cf-img').fadeIn();
        });
        //alert("Left:" + left + "Middle:" + mid + "Right:" + right + "");
    }
});

I think this is the function within the plugin that I need to get my code into, but I can't see how it works.
        function go(to) {
        if(!running) {

            if(o.beforeStart)
                o.beforeStart.call(this, vis());

            if(o.circular) {            // If circular we are in first or last, then goto the other end
                if(to<=o.start-v-1) {           // If first, then goto last
                    ul.css(animCss, -((itemLength-(v*2))*liSize)+"px");
                    // If "scroll" > 1, then the "to" might not be equal to the condition; it can be lesser depending on the number of elements.
                    curr = to==o.start-v-1 ? itemLength-(v*2)-1 : itemLength-(v*2)-o.scroll;
                    //alert (curr);
                } else if(to>=itemLength-v+1) { // If last, then goto first
                    ul.css(animCss, -( (v) * liSize ) + "px" );
                    // If "scroll" > 1, then the "to" might not be equal to the condition; it can be greater depending on the number of elements.
                    curr = to==itemLength-v+1 ? v+1 : v+o.scroll;
                    //alert (curr);
                } else {
                    curr = to;
                    //alert (curr);
                }
            } else {                    // If non-circular and to points to first or last, we just return.
                if(to<0 || to>itemLength-v) return;
                else curr = to;
            }                           // If neither overrides it, the curr will still be "to" and we can proceed.

            running = true;

            ul.animate(
                animCss == "left" ? { left: -(curr*liSize) } : { top: -(curr*liSize) } , o.speed, o.easing,
                function() {
                    //alert (curr-2);
                    if(o.afterEnd)
                        o.afterEnd.call(this, vis());
                    running = false;
                }
            );
            // Disable buttons when the carousel reaches the last/first, and enable when not
            if(!o.circular) {
                $(o.btnPrev + "," + o.btnNext).removeClass("disabled");
                $( (curr-o.scroll<0 && o.btnPrev)
                    ||
                   (curr+o.scroll > itemLength-v && o.btnNext)
                    ||
                   []
                 ).addClass("disabled");
            }

        }
        return false;
    };

A: I think this will help you:
How to get the current index with jCarousel Lite?
In addition to the above article I've set line 241 to the following
div.css({position: "relative", "z-index": "2", left: "-1144px"}); //changed the left from 0 to -1144px to allow the carousel circle to repeat offscreen

This shifts the entire carousel left. In my case I'm shifting the carousel 1144px because I have set width slides but you could just as easily calculate the left offset dynamically.
Now that I have 2 slides offscreen left I set the .jCarouselLite({ visible: 6 }); this gives me 2 visible slides in the middle and another two offscreen right.
Next place the following code anywhere after the ul.animate();
li.eq(curr+1).addClass("prev");
li.eq(curr+2).addClass("current");
li.eq(curr+3).addClass("next");

Lastly be sure to set the proper index slide to current. Following the guidelines of the linked article I'm actually starting my carousel on index 8
$(".jCarouselLite li").eq(7).addClass("prev");
$(".jCarouselLite li").eq(8).addClass("current");
$(".jCarouselLite li").eq(9).addClass("next");

To try and figure out a little more about the jCarousel Lite script you've outlined above try placing alert(curr); or console.log(curr); after each of the "if(o." areas. If all goes well you'll get the index of the current slide.


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Home News Briefs VC-backed Roofstock recruits Babaria as chief product officer
VC-backed Roofstock recruits Babaria as chief product officer
Iris Dorbian
Roofstock, a real estate investment marketplace, has named Ketan Babaria as chief product officer. Babaria is the former product head for LifeLock and Capital One's D3 incubation unit. Roofstock is backed by Khosla Ventures, Lightspeed Venture Partners, Bain Capital Ventures and Canvas Ventures.
Correction: An earlier version of this headline and news report misspelled Babaria. The name has since been corrected.
OAKLAND, Calif.–(BUSINESS WIRE)–Roofstock, the leading marketplace for investing in real estate, announced the addition of Ketan Babaria to the fintech's leadership team as Chief Product Officer. Formerly the Head of Product for LifeLock and Capital One's D3 incubation unit, Babaria will enhance Roofstock's current offerings and introduce new, creative ideas to accelerate the fintech's growth and make real estate investing radically accessible.
"Ketan built his career scaling high-growth companies and breaking new ground to multiply the impact of companies and their products. He has a unique talent for combining big-picture creativity with leadership savvy and analytical rigor to turn big ideas into reality," said Gary Beasley, CEO and Co-Founder of Roofstock.
Babaria joins Roofstock with nearly two decades of product innovation and leadership experience at financial services and consumer companies including LifeLock (acquired by Symantec), Capital One, PayPal and eBay.
As Head of Product at LifeLock, Babaria oversaw an $800+ million product portfolio and led product innovation efforts. This included launching LifeLock's international initiative and identity protection services. Babaria also held the position of Senior Director and Head of Product at Capital One, where he pioneered a data-driven mobile product that leveraged machine learning to offer personalized recommendations to cardholders.
"Roofstock has reached an exciting phase in our growth," said Gregor Watson, Chairman and Co-Founder of Roofstock. "Ketan will accelerate our momentum and advance our mission to make it radically simple to build wealth with real estate."
The fintech combines the leadership savvy and entrepreneurial visions of industry veterans Gary Beasley, Gregor Watson and Rich Ford, with a cutting edge team of product innovators, data scientists and engineers. Babaria joins the team to lead product development and reimagine the future of real estate investing for a new generation of investors.
"As a real estate investor myself, I've seen firsthand the inefficiencies and barriers everyday investors face. Roofstock is solving a major market inefficiency and modernizing a legacy industry with a tech-enabled marketplace unlike anything else out there," said Ketan Babaria. "As Chief Product Officer, I plan to take a data-driven and customer-first approach to lead the product team and take Roofstock to the next level."
Babaria joins Roofstock during a period of rapid innovation. The fintech made headlines in 2019 for being the first-to-market with a fractionalized investment offering in the single-family rental space, Roofstock One. With Roofstock One, accredited investors can purchase shares of fully-managed rental homes for as little as $5,000. The unique model redefines the meaning of homeownership, removes the hassles or responsibilities typically associated with direct ownership and makes property investing closer to the seamless experience of owning a stock.
"Roofstock has quickly established itself as a game-changer for real estate investors. The addition of Ketan as Chief Product Officer to the team will undoubtedly accelerate the fintech's already extraordinary pace of innovation and growth," said Will Kohler of Lightspeed Ventures.
Babaria earned an MBA from the University of California at Berkeley. He also has an MS in Systems Engineering from the University of Maryland and a BS in Ocean Engineering & Naval Architecture from the Indian Institute of Technology.
About Roofstock
Roofstock is the leading marketplace for investing in real estate, offering investment properties in top U.S.markets. The company provides all of the resources for investors to buy, own and sell real estate online, including data analytics, property management oversight, and other tools. Roofstock's transparent, innovative marketplace empowers investors to own cash-flowing rental properties, diversify their investment portfolios and build long-term wealth through real estate.
Backed by world-class investors including Khosla Ventures, Lightspeed Venture Partners, Bain Capital Ventures, and Canvas Ventures, Roofstock has received numerous accolades for its innovations in the real estate industry, including earning a spot on the 2019 Forbes Fintech 50 list and being recognized as "Best Real Estate Platform" at the Benzinga Fintech Awards in 2018. Within two years of launch in early 2016, the Oakland, California-based company eclipsed $1 billion in transaction volume.


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We look forward to seeing the visitors and telling them about our new online shop <here> - as well as selling our multi-award-winning Russian pies especially for those wanting a tasty and discounted lunch !


Project is estimated to begin upon signature or online registration submission and initial payment.
Please note, once sponsoring funds have been implemented there are no refunds.
Choose your option, click on the Add To Cart Button once you complete your payment information you will be taken to a information intake form that will provide us with the information needed to set up your Sponsorship Marketing Package.


Model teams are facing increased efforts to move faster and perform more efficiently to deliver and support projects and programme. They need high-quality frameworks, policies and procedures that meet regulatory standards and pass regulatory scrutiny. We can help you assess, perform gap analysis and roadmap development in these model-related areas.


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Friends That Sh*t On You…
Manly Cupcakes Cause Shrinkage
February 22, 2010 Guy Stuff
Sex.com: Up For Sale, But Does Sex Still Sell?
After selling for $14 million four years ago to Escom, the brutal battle for the most coveted domain name continues. Sex.com, one of the most expensive domains on the internet and the subject of not one, but two books, is up for sale yet again. Embarking on a 16-year battle, for the first 2 years Sex.com was owned by Gary Kremen the founder of the dating site Match.com until ownership was transferred to Stephen Cohen in what has been described as an elaborate scam. After a bitter 10 year court battle, Kremen eventually won back the rights to his domain and $65 million in damages. Escom recently defaulted on its debt forcing the sale of Sex.com next month. Once the most valuable piece of virtual real-estate on the planet, for the first five years, Sex.com had five million hits a day and generated $100 million a year.
Unplugg more on the story here.
Tags dating site Does Sex Still Sell Escom gary kremen match.com sex.com stephen cohen virtual real estate
Author Name: Tam
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